Predicting peptide receptor radiotherapy using a gene expression assay

ABSTRACT

The present invention is directed to methods for providing a peptide receptor radiotherapy treatment recommendation for a subject having a neuroendocrine tumor by determining the expression level of each of at least 9 biomarkers comprising ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, and ALG9. In some embodiments, the methods can further include determining the expression level of each of NAP1L1, NOL3, and TECPR2.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to, and the benefit of, U.S. Provisional Application No. 62/592,647, filed Nov. 30, 2017, the contents of which is incorporated herein by reference in its entirety.

SEQUENCE LISTING

The instant application contains a Sequence Listing which has been submitted in ASCII format via EFS-Web and is hereby incorporated by reference in its entirety. Said ASCII copy, created on Nov. 15, 2018, is named “LBIO-003_001US_ST25.txt” and is 52,601 bytes in size.

FIELD OF THE INVENTION

The present invention relates to the prediction of response to peptide receptor radiotherapy (PRRT) using a gene expression assay.

BACKGROUND OF THE INVENTION

The most commonly used form of radionuclide therapy in neuroendocrine tumors is peptide receptor radionuclide therapy (PRRT). This utilizes the overexpression of somatostatin receptors that are a central feature of NETs. PRRT uses an analog of somatostatin, octreotide, as a peptide to target the receptors. Radiolabeled derivatives of this analog include ¹⁷⁷Lu-DOTA-Tyr³,Thr⁸-octreotide or ¹⁷⁷Lu-octreotate. This therapeutic strategy is widely used in Europe and has more recently been introduced into the USA.

Diverse non-controlled studies in pancreatic and broncho-pulmonary NETs have demonstrated that ¹⁷⁷Lu-octreotate is effective with objective responses and a positive impact on survival parameters. Most recently a phase III, randomized, controlled trial of midgut NETs progressive on standard octreotide LAR treatment (NETTER-1) demonstrated ¹⁷⁷Lu-octreotate to be more effective than high-dose octreotide somatostatin analogs.

The decision to use PRRT is currently made on the basis of somatostatin receptor (SSR) expression levels. Information is usually obtained either by tissue biopsy and immunohistochemistry or by a somatostatin-based scan like an ¹¹¹In-pentetreotide scan or a ⁶⁸Ga-DOTATATE/DOTATOC PET/CT.

Immunohistochemistry is, however, limited since somatostatin receptor expression is heterogeneous in tumors, individual antibodies can have different binding affinities and assessment of staining by a pathologist does not provide an objective output. Further limiting factors include the inability to define receptor functionality and to determine expression in other tumors that are not biopsied.

Assessment of somatostatin expression using imaging involves comparing a radioactive uptake on a target lesion with a non-tumor organ like the spleen. The degree of uptake is graded from low to intensely positive per the Krenning grade. This approach has low predictive activity, however. For example, an intensely positive tumor—Krenning grade 4, at ¹¹¹In-pentetreotide scan—only has a 60% accuracy of responding. Various semi-quantitative tools have been attempted but all have failed. Somatostatin receptor expression is useful for identifying whether a tumor can be targetable and isotope delivered but it does not provide an accurate assessment of the likelihood of radiation susceptibility (and therapeutic efficacy).

Other clinical parameters (such as extent of disease), tumor grading and biomarkers (such as chromogranin A) have been investigated as potential predictive tools. None, however, have proven effective as robust predictors of the effect of therapy, although grading using morphological criteria or KI67 evaluation has demonstrated some clinical utility. The accuracy of grading is about 70% for predicting PRRT. Typically, low grade tumors (well-differentiated grade 1 or 2 i.e., KI67 detectable in ≤20% of tumor cells) respond to PRRT more often than high grade (KI67>20%) tumors. Grading, however, is limited by tumor heterogeneity, subjective observer variations and a low kappa value. Furthermore, tissue biopsies are rarely obtained from more than one location and metastases often differ significantly from the primary lesion biopsied for diagnosis.

It is evident that the complexity of the molecular drivers in tumor cells that define responsiveness to therapy in cancer or disease progression require more sophisticated assessment tools. The development of technologies based upon the delineation of the molecular biology of diverse cancers has led to the evolution of strategies to evaluate circulating molecular information emanating from neoplasia. Such strategies or “liquid biopsies”, have proven remarkably effective in lung neoplasia e.g., for monitoring treatment responses to EFGR inhibitors through identification of mutation T790M in circulating tumor DNA. The opportunity to limit biopsies, define potential therapeutic targets and to provide a real-time monitoring tool to evaluate disease evolution has considerable clinical allure.

SUMMARY OF THE INVENTION

The present disclosure provides a method of providing a peptide receptor radiotherapy (PRRT) treatment recommendation for a subject having a neuroendocrine tumor (NET), the method comprising: determining the expression level of at least 9 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 9 biomarkers, wherein the 9 biomarkers comprise ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, and ALG9; normalizing the expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, and PLD3 to the expression level of ALG9, thereby obtaining a normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, and PLD3; summing the normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, and PLD3, thereby obtaining a summated expression level; determining a first score, wherein the first score is 1 when the summated expression level is equal to or greater than a first predetermined cutoff value, or the first score is 0 when the summated expression level is below the first predetermined cutoff value; determining a second score based on the histological grade of the NET, wherein the second score is 1 when the NET is designated high grade, or the second score is 0 when the NET is designated low grade; calculating a third score based on the following equation: Third Score=39.22787−40.80341*(First Score)−18.441*(Second Score); and providing a recommendation that the NET will respond to PRRT when the third score is equal to or less than a second predetermined cutoff value, or providing a recommendation that the NET will not respond to PRRT when the third score is above the second predetermined cutoff value.

In the preceding method of the present disclosure, a first predetermined cutoff value can be 5.9. The second predetermined cutoff value can be 0.

The present disclosure provides a method of providing a peptide receptor radiotherapy (PRRT) treatment recommendation for a subject having a neuroendocrine tumor (NET), the method comprising: determining the expression level of at least 12 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 12 biomarkers, wherein the 12 biomarkers comprise ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, TECPR2, and ALG9; normalizing the expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2 to the expression level of ALG9, thereby obtaining a normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2; summing the normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2 PLD3, NAP1L1, NOL3, and TECPR2, thereby obtaining a summated expression level; determining a first score, wherein the first score is 1 when the summated expression level is equal to or greater than a first predetermined cutoff value, or the first score is 0 when the summated expression level is below the first predetermined cutoff value; determining a second score based on the histological grade of the NET, wherein the second score is 1 when the NET is designated high grade, or the second score is 0 when the NET is designated low grade; calculating a third score based on the following equation: Third Score=39.22787−40.80341*(First Score)−18.441*(Second Score); and providing a recommendation that the NET will respond to PRRT when the third score is equal to or less than a second predetermined cutoff value, or providing a recommendation that the NET will not respond to PRRT when the third score is above the second predetermined cutoff value.

In the preceding method of the present disclosure, a first predetermined cutoff value can be 10.9. A second predetermined cutoff value can be 0.

The present disclosure provides a method of providing a peptide receptor radiotherapy (PRRT) treatment recommendation for a subject having a neuroendocrine tumor (NET), the method comprising: determining the expression level of each of at least 12 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 12 biomarkers, wherein the 12 biomarkers comprise ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, TECPR2, and ALG9; normalizing the expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2 to the expression level of ALG9, thereby obtaining a normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2; summing the normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2 thereby obtaining a summated expression level; and providing a recommendation that the NET will respond to PRRT when the summated expression level is equal to or greater than a predetermined cutoff value, or providing a recommendation that the NET will not respond to PRRT when the summated expression level is less than the predetermined cutoff value.

In the preceding method of the present disclosure, the predetermined cutoff value can be 10.9.

The present disclosure provides a method of providing a peptide receptor radiotherapy (PRRT) treatment recommendation for a subject having a low grade or high grade neuroendocrine tumor (NET), the method comprising: determining the expression level of each of at least 12 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 12 biomarkers, wherein the 12 biomarkers comprise ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, TECPR2, and ALG9; normalizing the expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2 to the expression level of ALG9, thereby obtaining a normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2; summing the normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2, thereby obtaining a summated expression level; and providing a recommendation that the low grade or high grade NET will respond to PRRT when the summated expression level is equal to or greater than a predetermined cutoff value, or providing a recommendation that the low grade or high grade NET will not respond to PRRT when the summated expression level is less than the predetermined cutoff value.

In the preceding method of the present disclosure, wherein the predetermined cutoff value cam be 10.9.

The present disclosure provides a method of providing a peptide receptor radiotherapy (PRRT) treatment recommendation for a subject having a low grade or high grade neuroendocrine tumor (NET), the method comprising: determining the expression level of each of at least 9 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 9 biomarkers, wherein the 9 biomarkers comprise ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, and ALG9; normalizing the expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, and PLD3 to the expression level of ALG9, thereby obtaining a normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, and PLD3; summing the normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, and PLD3, thereby obtaining a summated expression level; and providing a recommendation that the low grade or high grade NET will respond to PRRT when the summated expression level is equal to or greater than a predetermined cutoff value, or providing a recommendation that the low grade or high grade NET will not respond to PRRT when the summated expression level is less than the predetermined cutoff value.

In methods of the present disclosure, at least one of the at least 9 biomarkers can be RNA, cDNA, or protein. In aspects wherein a biomarker is RNA, the RNA can be reverse transcribed to produce cDNA, and the produced cDNA expression level can be detected. In aspects wherein a biomarker is protein, the protein can be detected by forming a complex between the biomarker and a labeled probe or primer.

In methods of the present disclosure, expression level of a biomarker can be detected by forming a complex between a biomarker and a labeled probe or primer.

In methods of the present disclosure, when a biomarker is RNA or cDNA, the RNA or cDNA can be detected by forming a complex between the RNA or cDNA and a labeled nucleic acid probe or primer. A complex between the RNA or cDNA and the labeled nucleic acid probe or primer can be a hybridization complex.

In methods of the present disclosure, a test sample can be blood, serum, plasma, or neoplastic tissue. In methods of the present disclosure, the test sample can be blood.

In methods of the present disclosure, a NET can be designated high grade when the NET is poorly differentiated.

In methods of the present disclosure, a NET can be designated low grade when the NET is well differentiated, bronchial typical carcinoid, or bronchial atypical carcinoid.

Methods of the present disclosure can further comprise administering PRRT to the subject when the third score is equal to or less than the second predetermined cutoff value.

Methods of the present disclosure can further comprise administering PRRT to the subject when the summated expression level is equal to or greater than the predetermined cutoff value.

Methods of the present disclosure can have a sensitivity of greater than 90%. Methods of the present disclosure can have a specificity of greater than 90%.

The present disclosure provides a method of treating a subject with peptide receptor radiotherapy (PRRT), wherein the subject has a neuroendocrine tumor (NET), the method comprising: determining the expression level of at least 9 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 9 biomarkers, wherein the 9 biomarkers comprise ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, and ALG9; normalizing the expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, and PLD3 to the expression level of ALG9, thereby obtaining a normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, and PLD3; summing the normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, and PLD3, thereby obtaining a summated expression level; determining a first score, wherein the first score is 1 when the summated expression level is equal to or greater than a first predetermined cutoff value, or the first score is 0 when the summated expression level is below the first predetermined cutoff value; determining a second score based on the histological grade of the NET, wherein the second score is 1 when the NET is designated high grade, or the second score is 0 when the NET is designated low grade; calculating a third score based on the following equation: Third Score=39.22787−40.80341*(First Score)−18.441*(Second Score); and administering PRRT to the subject when the third score is equal to or greater than the predetermined cutoff value.

The present disclosure provides a method of treating a subject with peptide receptor radiotherapy (PRRT), wherein the subject has a neuroendocrine tumor (NET), the method comprising: determining the expression level of at least 12 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 12 biomarkers, wherein the 12 biomarkers comprise ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, TECPR2, and ALG9; normalizing the expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2 to the expression level of ALG9, thereby obtaining a normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2; summing the normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2 PLD3, NAP1L1, NOL3, and TECPR2, thereby obtaining a summated expression level; determining a first score, wherein the first score is 1 when the summated expression level is equal to or greater than a first predetermined cutoff value, or the first score is 0 when the summated expression level is below the first predetermined cutoff value; determining a second score based on the histological grade of the NET, wherein the second score is 1 when the NET is designated high grade, or the second score is 0 when the NET is designated low grade; calculating a third score based on the following equation: Third Score=39.22787−40.80341*(First Score)−18.441*(Second Score); and administering PRRT to the subject when the third score is equal to or greater than the predetermined cutoff value.

The present disclosure provides a method of treating a subject with peptide receptor radiotherapy (PRRT), wherein the subject has a neuroendocrine tumor (NET), the method comprising: determining the expression level of each of at least 12 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 12 biomarkers, wherein the 12 biomarkers comprise ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, TECPR2, and ALG9; normalizing the expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2 to the expression level of ALG9, thereby obtaining a normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2; summing the normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2 thereby obtaining a summated expression level; and administering PRRT to the subject when the summated expression level is equal to or greater than the predetermined cutoff value.

The present disclosure provides a method of treating a subject with peptide receptor radiotherapy (PRRT), wherein the subject has a low grade or high grade neuroendocrine tumor (NET), the method comprising: determining the expression level of each of at least 12 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 12 biomarkers, wherein the 12 biomarkers comprise ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, TECPR2, and ALG9; normalizing the expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2 to the expression level of ALG9, thereby obtaining a normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2; summing the normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2, thereby obtaining a summated expression level; and administering PRRT to the subject when the summated expression level is equal to or greater than the predetermined cutoff value.

The present disclosure provides a method of treating a subject with peptide receptor radiotherapy (PRRT), wherein the subject has a low grade or high grade neuroendocrine tumor (NET), the method comprising: determining the expression level of each of at least 9 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 9 biomarkers, wherein the 9 biomarkers comprise ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, and ALG9; normalizing the expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, and PLD3 to the expression level of ALG9, thereby obtaining a normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, and PLD3; summing the normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, and PLD3, thereby obtaining a summated expression level; and administering PRRT to the subject when the summated expression level is equal to or greater than the predetermined cutoff value.

In methods of the present disclosure, administering PRRT to the subject can comprise administering a ¹⁷⁷Lu-based-PRRT. A ¹⁷⁷Lu-based-PRRT can be ¹⁷⁷Lu-DOTA-Tyr³-Thr⁸-octreotide.

In methods of the present disclosure, ¹⁷⁷Lu-DOTA-Tyr³-Thr⁸-octreotide can be administered at a dose of about 7.4 GBq (200 mCi) about once every 8 weeks for a total of about 4 doses. ¹⁷⁷Lu-DOTA-Tyr³-Thr⁸-octreotide can be administered at a dose of about 6.5 GBq about once every 8 weeks for a total of about 4 doses. ¹⁷⁷Lu-DOTA-Tyr³-Thr⁸-octreotide can be administered at a dose of about 4.6 GBq about once every 8 weeks for a total of about 4 doses.

¹⁷⁷Lu-DOTA-Tyr³-Thr⁸-octreotide can be administered at a dose of about 3.2 GBq (100 mCi) about once every 8 weeks for a total of about 4 doses. ¹⁷⁷Lu-DOTA-Tyr³-Thr⁸-octreotide can be administered at a dose of about 3.7 GBq about once every 8 weeks for a total of about 4 doses.

In methods of the present disclosure, ¹⁷⁷Lu-based-PRRT can be administered intravenously. ¹⁷⁷Lu-based-PRRT can be administered intra-arterially.

In some embodiments of any one of the above aspects, the method further comprises administering PRRT to the subject when it's predicted that the NET will respond to PRRT.

Any of the above aspects can be combined with any other aspect.

Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. In the Specification, the singular forms also include the plural unless the context clearly dictates otherwise; as examples, the terms “a,” “an,” and “the” are understood to be singular or plural and the term “or” is understood to be inclusive. By way of example, “an element” means one or more element. Throughout the specification the word “comprising,” or variations such as “comprises” or “comprising,” will be understood to imply the inclusion of a stated element, integer or step, or group of elements, integers or steps, but not the exclusion of any other element, integer or step, or group of elements, integers or steps. About can be understood as within 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2%, 1%, 0.5%, 0.1%, 0.05%, or 0.01% of the stated value. Unless otherwise clear from the context, all numerical values provided herein are modified by the term “about.”

Although methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present disclosure, suitable methods and materials are described below. All publications, patent applications, patents, and other references mentioned herein are incorporated by reference in their entirety. The references cited herein are not admitted to be prior art to the claimed invention. In the case of conflict, the present Specification, including definitions, will control. In addition, the materials, methods, and examples are illustrative only and are not intended to be limiting. Other features and advantages of the disclosure will be apparent from the following detailed description and claim.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a graph showing the utility of the PRRT prediction quotient for predicting PFS in the test cohort. Test cohort (n=72): In patients predicted to respond pre-therapy by the PPQ (biomarker positive), mPFS was not reached. For those predicted not to respond (biomarker negative), the mPFS was 8 months. This was significantly different (HR 36.4, p<0.0001).

FIG. 2 is a graph showing the utility of the PRRT Prediction Quotient for predicting PFS in Validation Cohort I. The mPFS was not reached in those predicted to respond. In those predicted not to respond, the mPFS was 14 months (HR 17.7, p<0.0001).

FIG. 3 is a graph showing the utility of the PRRT Prediction Quotient for predicting PFS in Validation Cohort II. In prediction-responders, the mPFS was not reached. For those predicted not to respond, the mPFS was 9.7 months. This was significantly different (HR 92, p<0.0001).

FIG. 4 is a graph showing the utility of the PRRT prediction quotient for predicting PFS in SSA treated patients. In prediction-responders, the mPFS was 10 months. For those predicted not to respond, the mPFS was not reached. This was not significantly different (HR 0.8, p=NS).

FIG. 5 is a graph showing the utility of the PRRT Prediction Quotient for predicting PFS in Registry-enrolled patients. In prediction-responders, the mPFS was 10 months. For those predicted not to respond, the mPFS was 15. This was not significantly different (HR 0.9, p=NS).

FIGS. 6A-6D are graphs showing demonstration of utility of the PPQ as a predictive marker.

FIG. 6A shows PPQ in PRRT and comparator cohorts in Biomarker positive cases. In prediction-responders i.e., PPQ “positive” groups, the mPFS was not reached in PRRT treated patients (Validation Cohort I (n=44) and Validation Cohort II (n=42) compared to those treated with SSAs or in the Registry.

FIG. 6B shows PPQ in PRRT and comparator cohorts in Biomarker negative cases: In prediction-non-responders i.e., PPQ “negative” groups, the mPFS was similar irrespective of treatment with PRRT or not.

FIG. 6C shows ideal Predictive Biomarker “Positive”: In this idealized example, a “treatment effect” i.e., a quantitative difference in mPFS is noted between those undergoing treatment (mPFS undefined) and those not undergoing treatment (17 months).

FIG. 6D shows ideal Predictive Biomarker “Negative”: In this idealized example, the mPFS is the same (18 months) irrespective of treatment.

FIG. 7 shows the progression-free survival (PFS) of PPQ negative subjects after treatment with PRRT or a combination of PRRT and chemotherapy.

DETAILED DESCRIPTION OF THE INVENTION

The details of the invention are set forth in the accompanying description below. Although methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, illustrative methods and materials are now described. Other features, objects, and advantages of the invention will be apparent from the description and from the claims. In the specification and the appended claims, the singular forms also include the plural unless the context clearly dictates otherwise. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. All patents and publications cited in this specification are incorporated herein by reference in their entireties.

This invention is based, in part, on the discovery that the expression levels of circulating neuroendocrine tumor (NET) transcripts can predict whether a patient with a NET will respond to peptide receptor radiotherapy (PRRT). The circulating NET transcripts include the following: (a) growth factor (GF)-related genes (ARAF1, BRAF, KRAS and RAF-1); and (b) genes involved in metabolism (M) (ATP6V1H, OAZ2, PANK2 and PLD3). The expression levels of these genes can be normalized to ALG9, which serves as a housekeeping gene. It was discovered that when the summated expression level (post normalization) of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3 is equal to or greater than a predetermined cutoff value, the NET will respond to PRRT, regardless of the histological grade of the NET. In addition, when the summated expression level (post normalization) of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3 is less than a predetermined cutoff value, the NET will not respond to PRRT, regardless of the histological grade of the NET. In some embodiments, the circulating NET transcripts can further include genes involved in proliferation (P) (NAP1L1, NOL3, and TECPR2). The expression levels of NAP1L1, NOL3, and TECPR2 can also be measured and normalized to the expression level of ALG9.

In some embodiments, the summated expression level of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3 can be obtained by implementing the following steps: (a1) determining the expression level of each of at least 9 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 9 biomarkers, wherein the 9 biomarkers comprise ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, and ALG9; (b1) normalizing the expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, and PLD3 to the expression level of ALG9, thereby obtaining a normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, and PLD3; and (c1) summing the normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, and PLD3, thereby obtaining a summated expression level.

Alternatively, the summated expression level of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3 can also be obtained by implementing the following steps after the expression level of each of the at least 9 biomarkers is determined: (a2) summing the expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, and PLD3, thereby obtaining a summated value; and (b2) normalizing the summated value to the expression level of ALG9, thereby obtaining a summated expression level.

One aspect of the present disclosure provides a method of providing a PRRT treatment recommendation for a subject having a low grade or high grade NET, the method comprising providing a recommendation that the low grade or high grade NET will respond to PRRT when the summated expression level of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3 is equal to or greater than a predetermined cutoff value, or providing a recommendation that the low grade or high grade NET will not respond to PRRT when the summated expression level is less than the predetermined cutoff value. In some embodiments, the NET is designated high grade when the NET is poorly differentiated. In some embodiments, the NET is designated low grade when the NET is well differentiated, bronchial typical carcinoid, or bronchial atypical carcinoid.

In a similar aspect, the present disclosure provides a method of providing a PRRT treatment recommendation for a subject having a NET, the method comprising providing a recommendation that the NET will respond to PRRT when the summated expression level of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3 is equal to or greater than a predetermined cutoff value, or providing a recommendation that the NET will not respond to PRRT when the summated expression level is less than the predetermined cutoff value.

In some embodiments, the predetermined cutoff value is 5.9. This cutoff value is derived from a scenario where the summated expression level of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3 is 5.9 times the expression level of ALG9.

In another aspect, the histological grade of the NET can also be used in conjunction with the expression levels of the circulating neuroendocrine tumor transcripts. Accordingly, the present disclosure provides a method of providing a PRRT treatment recommendation for a subject having a NET, the method comprising: (a3) determining a first score, wherein the first score is 1 when the summated expression level of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3 is equal to or greater than a first predetermined cutoff value, or the first score is 0 when the summated expression level is below the first predetermined cutoff value; (b3) determining a second score based on the histological grade of the NET, wherein the second score is 1 when the NET is designated high grade, or the second score is 0 when the NET is designated low grade; (c3) calculating a third score based on the following equation: Third Score=39.22787−40.80341*(First Score)−18.441*(Second Score); and (d3) providing a recommendation that the NET will respond to PRRT when the third score is equal to or less than a second predetermined cutoff value, or providing a recommendation that the NET will not respond to PRRT when the third score is above the second predetermined cutoff value.

In some embodiments, the first predetermined cutoff value is 5.9. This cutoff value is derived from a scenario where the summated expression level of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3 is 5.9 times the expression level of ALG9.

In some embodiments, the second predetermined cutoff value is 0.

In one aspect, the present disclosure provides a method of providing a PRRT treatment recommendation for a subject having a low grade or high grade NET, the method comprising: (a) determining the expression level of each of at least 12 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 12 biomarkers, wherein the 12 biomarkers comprise ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, TECPR2, and ALG9; (b) normalizing the expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2 to the expression level of ALG9, thereby obtaining a normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2; (c) summing the normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2, thereby obtaining a summated expression level; and (d) providing a recommendation that the low grade or high grade NET will respond to PRRT when the summated expression level is equal to or greater than a predetermined cutoff value, or providing a recommendation that the low grade or high grade NET will not respond to PRRT when the summated expression level is less than the predetermined cutoff value. In some embodiments, the predetermined cutoff value is 10.9.

In another aspect, the present disclosure provides a method of providing a PRRT treatment recommendation for a subject having a NET, the method comprising: (a) determining the expression level of each of at least 12 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 12 biomarkers, wherein the 12 biomarkers comprise ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, TECPR2, and ALG9; (b) normalizing the expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2 to the expression level of ALG9, thereby obtaining a normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2; (c) summing the normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2 thereby obtaining a summated expression level; and (d) providing a recommendation that the NET will respond to PRRT when the summated expression level is equal to or greater than a predetermined cutoff value, or providing a recommendation that the NET will not respond to PRRT when the summated expression level is less than the predetermined cutoff value. In some embodiments, the predetermined cutoff value is 10.9.

In another aspect, the present disclosure provides a method of providing a PRRT treatment recommendation for a subject having a NET, the method comprising: (a) determining the expression level of at least 12 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 12 biomarkers, wherein the 12 biomarkers comprise ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, TECPR2, and ALG9; (b) normalizing the expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2 to the expression level of ALG9, thereby obtaining a normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2; (c) summing the normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2 PLD3, NAP1L1, NOL3, and TECPR2, thereby obtaining a summated expression level; (d) determining a first score, wherein the first score is 1 when the summated expression level is equal to or greater than a first predetermined cutoff value, or the first score is 0 when the summated expression level is below the first predetermined cutoff value; (e) determining a second score based on the histological grade of the NET, wherein the second score is 1 when the NET is designated high grade, or the second score is 0 when the NET is designated low grade; (f) calculating a third score based on the following equation: Third Score=39.22787−40.80341*(First Score)−18.441*(Second Score); and (f) providing a recommendation that the NET will respond to PRRT when the third score is equal to or less than a second predetermined cutoff value, or providing a recommendation that the NET will not respond to PRRT when the third score is above the second predetermined cutoff value. In some embodiments, the first predetermined cutoff value is 10.9. In some embodiments, the second predetermined cutoff value is 0.

A responder (i.e., the NET will respond to PRRT) refers to an individual predicted by the methods described herein as achieving disease stabilization or demonstrating a partial response. A non-responder (i.e., the NET will not respond to PRRT) refers to an individual exhibiting progressive disease.

The test sample can be any biological fluid obtained from the subject. Preferably, the test sample is blood, serum, plasma or neoplastic tissue. In some embodiments, the test sample is blood. In some embodiments, the test sample is serum. In some embodiments, the test sample is plasma.

The expression level can be measured in a number of ways, including, but not limited to: measuring the mRNA encoded by the selected genes; measuring the amount of protein encoded by the selected genes; and measuring the activity of the protein encoded by the selected genes.

The biomarker can be RNA, cDNA, or protein. When the biomarker is RNA, the RNA can be reverse transcribed to produce cDNA (such as by RT-PCR, and the produced cDNA expression level is detected. The expression level of the biomarker can be detected by forming a complex between the biomarker and a labeled probe or primer. When the biomarker is RNA or cDNA, the RNA or cDNA detected by forming a complex between the RNA or cDNA and a labeled nucleic acid probe or primer. The complex between the RNA or cDNA and the labeled nucleic acid probe or primer can be a hybridization complex.

Gene expression can also be detected by microarray analysis. Differential gene expression can also be identified, or confirmed using the microarray technique. Thus, the expression profile biomarkers can be measured in either fresh or fixed tissue, using microarray technology. In this method, polynucleotide sequences of interest (including cDNAs and oligonucleotides) are plated, or arrayed, on a microchip substrate. The arrayed sequences are then hybridized with specific DNA probes from cells or tissues of interest. The source of mRNA typically is total RNA isolated from a biological sample, and corresponding normal tissues or cell lines may be used to determine differential expression.

In some embodiments of the microarray technique, PCR amplified inserts of cDNA clones are applied to a substrate in a dense array. Preferably at least 10,000 nucleotide sequences are applied to the substrate. The microarrayed genes, immobilized on the microchip at 10,000 elements each, are suitable for hybridization under stringent conditions. Fluorescently labeled cDNA probes may be generated through incorporation of fluorescent nucleotides by reverse transcription of RNA extracted from tissues of interest. Labeled cDNA probes applied to the chip hybridize with specificity to each spot of DNA on the array. After stringent washing to remove non-specifically bound probes, the microarray chip is scanned by a device such as, confocal laser microscopy or by another detection method, such as a CCD camera. Quantitation of hybridization of each arrayed element allows for assessment of corresponding mRNA abundance. With dual color fluorescence, separately labeled cDNA probes generated from two sources of RNA are hybridized pair-wise to the array. The relative abundance of the transcripts from the two sources corresponding to each specified gene is thus determined simultaneously. Microarray analysis can be performed by commercially available equipment, following manufacturer's protocols.

In some embodiments, the biomarkers can be detected in a biological sample using qRT-PCR. The first step in gene expression profiling by RT-PCR is extracting RNA from a biological sample followed by the reverse transcription of the RNA template into cDNA and amplification by a PCR reaction. The reverse transcription reaction step is generally primed using specific primers, random hexamers, or oligo-dT primers, depending on the goal of expression profiling. The two commonly used reverse transcriptases are avilo myeloblastosis virus reverse transcriptase (AMV-RT) and Moloney murine leukemia virus reverse transcriptase (MLV-RT).

When the biomarker is protein, the protein can be detected by forming a complex between the protein and a labeled antibody. The label can be any label for example a fluorescent label, chemiluminescence label, radioactive label, etc. Exemplary methods for protein detection include, but are not limited to, enzyme immunoassay (EIA), radioimmunoassay (MA), Western blot analysis and enzyme linked immunoabsorbant assay (ELISA). For example, the biomarker can be detected in an ELISA, in which the biomarker antibody is bound to a solid phase and an enzyme-antibody conjugate is employed to detect and/or quantify biomarker present in a sample. Alternatively, a western blot assay can be used in which solubilized and separated biomarker is bound to nitrocellulose paper. The combination of a highly specific, stable liquid conjugate with a sensitive chromogenic substrate allows rapid and accurate identification of samples.

In some embodiments, the methods described herein further comprise administering PRRT to the subject when it's predicted that the NET will respond to PRRT. For example, in accordance with some aspects of the present disclosure, the method further comprises administering PRRT to the subject when the summated expression level is equal to or greater than the predetermined cutoff value. In accordance with other aspects of the present disclosure, the method further comprises administering PRRT to the subject when the third score is equal to or less than the second predetermined cutoff value. In PRRT, a cell-targeting protein (or peptide) called octreotide is combined with a small amount of radioactive material, or radionuclide, creating a special type of radiopharmaceutical called a radiopeptide. When injected into the patient's bloodstream, this radiopeptide travels to and binds to neuroendocrine tumor cells, delivering a high dose of radiation to the cancer.

When it's predicted that the NET will not respond to PRRT, the methods described herein further comprise monitoring the subject over a period of time, e.g., 1-6 months.

In some embodiments, the methods described herein can have a specificity, sensitivity, and/or accuracy of at least 75%, 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99%.

The present disclosure provides a method of treating a subject with peptide receptor radiotherapy (PRRT), wherein the subject has a neuroendocrine tumor (NET), the method comprising: determining the expression level of at least 9 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 9 biomarkers, wherein the 9 biomarkers comprise ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, and ALG9; normalizing the expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, and PLD3 to the expression level of ALG9, thereby obtaining a normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, and PLD3; summing the normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, and PLD3, thereby obtaining a summated expression level; determining a first score, wherein the first score is 1 when the summated expression level is equal to or greater than a first predetermined cutoff value, or the first score is 0 when the summated expression level is below the first predetermined cutoff value; determining a second score based on the histological grade of the NET, wherein the second score is 1 when the NET is designated high grade, or the second score is 0 when the NET is designated low grade; calculating a third score based on the following equation: Third Score=39.22787−40.80341*(First Score)−18.441*(Second Score); and administering PRRT to the subject when the third score is equal to or greater than the predetermined cutoff value.

The present disclosure provides a method of treating a subject with peptide receptor radiotherapy (PRRT), wherein the subject has a neuroendocrine tumor (NET), the method comprising: determining the expression level of at least 9 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 9 biomarkers, wherein the 9 biomarkers comprise ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, and ALG9; normalizing the expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, and PLD3 to the expression level of ALG9, thereby obtaining a normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, and PLD3; summing the normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, and PLD3, thereby obtaining a summated expression level; determining a first score, wherein the first score is 1 when the summated expression level is equal to or greater than a first predetermined cutoff value, or the first score is 0 when the summated expression level is below the first predetermined cutoff value; determining a second score based on the histological grade of the NET, wherein the second score is 1 when the NET is designated high grade, or the second score is 0 when the NET is designated low grade; calculating a third score based on the following equation: Third Score=39.22787−40.80341*(First Score)−18.441*(Second Score); and administering PRRT to the subject when the third score is equal to or greater than the predetermined cutoff value or administering an alternative form of therapy to the subject when the third score is less than the predetermined cutoff value.

The present disclosure provides a method of treating a subject with peptide receptor radiotherapy (PRRT), wherein the subject has a neuroendocrine tumor (NET), the method comprising: determining the expression level of at least 12 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 12 biomarkers, wherein the 12 biomarkers comprise ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, TECPR2, and ALG9; normalizing the expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2 to the expression level of ALG9, thereby obtaining a normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2; summing the normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2 PLD3, NAP1L1, NOL3, and TECPR2, thereby obtaining a summated expression level; determining a first score, wherein the first score is 1 when the summated expression level is equal to or greater than a first predetermined cutoff value, or the first score is 0 when the summated expression level is below the first predetermined cutoff value; determining a second score based on the histological grade of the NET, wherein the second score is 1 when the NET is designated high grade, or the second score is 0 when the NET is designated low grade; calculating a third score based on the following equation: Third Score=39.22787−40.80341*(First Score)−18.441*(Second Score); and administering PRRT to the subject when the third score is equal to or greater than the predetermined cutoff value.

The present disclosure provides a method of treating a subject with peptide receptor radiotherapy (PRRT), wherein the subject has a neuroendocrine tumor (NET), the method comprising: determining the expression level of at least 12 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 12 biomarkers, wherein the 12 biomarkers comprise ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, TECPR2, and ALG9; normalizing the expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2 to the expression level of ALG9, thereby obtaining a normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2; summing the normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2 PLD3, NAP1L1, NOL3, and TECPR2, thereby obtaining a summated expression level; determining a first score, wherein the first score is 1 when the summated expression level is equal to or greater than a first predetermined cutoff value, or the first score is 0 when the summated expression level is below the first predetermined cutoff value; determining a second score based on the histological grade of the NET, wherein the second score is 1 when the NET is designated high grade, or the second score is 0 when the NET is designated low grade; calculating a third score based on the following equation: Third Score=39.22787−40.80341*(First Score)−18.441*(Second Score); and administering PRRT to the subject when the third score is equal to or greater than the predetermined cutoff value or administering an alternative form of therapy to the subject when the third score is less than the predetermined cutoff value.

The present disclosure provides a method of treating a subject with peptide receptor radiotherapy (PRRT), wherein the subject has a neuroendocrine tumor (NET), the method comprising: determining the expression level of each of at least 12 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 12 biomarkers, wherein the 12 biomarkers comprise ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, TECPR2, and ALG9; normalizing the expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2 to the expression level of ALG9, thereby obtaining a normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2; summing the normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2 thereby obtaining a summated expression level; and administering PRRT to the subject when the summated expression level is equal to or greater than the predetermined cutoff value.

The present disclosure provides a method of treating a subject with peptide receptor radiotherapy (PRRT), wherein the subject has a neuroendocrine tumor (NET), the method comprising: determining the expression level of each of at least 12 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 12 biomarkers, wherein the 12 biomarkers comprise ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, TECPR2, and ALG9; normalizing the expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2 to the expression level of ALG9, thereby obtaining a normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2; summing the normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2 thereby obtaining a summated expression level; and administering PRRT to the subject when the summated expression level is equal to or greater than the predetermined cutoff value or administering an alternative form of therapy to the subject when the summated expression level is less than the predetermined cutoff value.

The present disclosure provides a method of treating a subject with peptide receptor radiotherapy (PRRT), wherein the subject has a low grade or high grade neuroendocrine tumor (NET), the method comprising: determining the expression level of each of at least 12 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 12 biomarkers, wherein the 12 biomarkers comprise ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, TECPR2, and ALG9; normalizing the expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2 to the expression level of ALG9, thereby obtaining a normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2; summing the normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2, thereby obtaining a summated expression level; and administering PRRT to the subject when the summated expression level is equal to or greater than the predetermined cutoff value.

The present disclosure provides a method of treating a subject with peptide receptor radiotherapy (PRRT), wherein the subject has a low grade or high grade neuroendocrine tumor (NET), the method comprising: determining the expression level of each of at least 12 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 12 biomarkers, wherein the 12 biomarkers comprise ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, TECPR2, and ALG9; normalizing the expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2 to the expression level of ALG9, thereby obtaining a normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2; summing the normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2, thereby obtaining a summated expression level; and administering PRRT to the subject when the summated expression level is equal to or greater than the predetermined cutoff value or administering an alternative form of therapy to the subject when the summated expression level is less than the predetermined cutoff value.

The present disclosure provides a method of treating a subject with peptide receptor radiotherapy (PRRT), wherein the subject has a low grade or high grade neuroendocrine tumor (NET), the method comprising: determining the expression level of each of at least 9 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 9 biomarkers, wherein the 9 biomarkers comprise ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, and ALG9; normalizing the expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, and PLD3 to the expression level of ALG9, thereby obtaining a normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, and PLD3; summing the normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, and PLD3, thereby obtaining a summated expression level; and administering PRRT to the subject when the summated expression level is equal to or greater than the predetermined cutoff value.

The present disclosure provides a method of treating a subject with peptide receptor radiotherapy (PRRT), wherein the subject has a low grade or high grade neuroendocrine tumor (NET), the method comprising: determining the expression level of each of at least 9 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 9 biomarkers, wherein the 9 biomarkers comprise ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, and ALG9; normalizing the expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, and PLD3 to the expression level of ALG9, thereby obtaining a normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, and PLD3; summing the normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, and PLD3, thereby obtaining a summated expression level; and administering PRRT to the subject when the summated expression level is equal to or greater than the predetermined cutoff value or administering an alternative form of therapy to the subject when the summated expression level is less than the predetermined cutoff value.

In methods of the present disclosure, administering PRRT to the subject can comprise administering a ¹⁷⁷Lu-based-PRRT. A ¹⁷⁷Lu-based-PRRT can be ¹⁷⁷Lu-DOTA-Tyr³-Thr⁸-octreotide (Lutathera).

In methods of the present disclosure, ¹⁷⁷Lu-DOTA-Tyr³-Thr⁸-octreotide can be administered at a dose of about 7.4 GBq (200 mCi) about once every 8 weeks for a total of about 4 doses. ¹⁷⁷Lu-DOTA-Tyr³-Thr⁸-octreotide can be administered at a dose of about 6.5 GBq about once every 8 weeks for a total of about 4 doses. ¹⁷⁷Lu-DOTA-Tyr³-Thr⁸-octreotide can be administered at a dose of about 4.6 GBq about once every 8 weeks for a total of about 4 doses. ¹⁷⁷Lu-DOTA-Tyr³-Thr⁸-octreotide can be administered at a dose of about 3.2 GBq (100 mCi) about once every 8 weeks for a total of about 4 doses. ¹⁷⁷Lu-DOTA-Tyr³-Thr⁸-octreotide can be administered at a dose of about 3.7 GBq about once every 8 weeks for a total of about 4 doses.

In methods of the present disclosure, PRRT can be administered intravenously. Alternatively, PRRT can be administered intra-arterially.

In methods of the present disclosure, ¹⁷⁷Lu-based-PRRT can be administered intravenously. Alternatively, ¹⁷⁷Lu-based-PRRT can be administered intra-arterially.

In methods of the present disclosure, an alternative form of therapy can comprise administering chemotherapy to a subject. An alternative form of therapy can comprise administering immunotherapy to a subject. An alternative form of therapy can comprise administering radiation therapy to a subject. An alternative form of therapy can comprise administering a combination of PRRT and chemotherapy to a subject. An alternative form of therapy can comprise administering a combination of PRRT and immunotherapy to a subject. An alternative form of therapy can comprise administering a combination of PRRT and radiation therapy to a subject. An alternative form of therapy can comprise administering a combination of PRRT, immunotherapy and chemotherapy to a subject. An alternative form of therapy can comprise administering a combination of PRRT, immunotherapy, chemotherapy and radiation therapy to a subject. An alternative form of therapy can comprise administering a combination of immunotherapy and chemotherapy to a subject.

Immunotherapy can comprise administering checkpoint inhibitors. Checkpoint inhibitors can comprise antibodies. Checkpoint inhibitors include, but are not limited to, anti-CTLA4 antibodies, anti-PD-1 antibodies, anti-PD-L1 antibodies, anti-AZAR antibodies, anti-B7-H3 antibodies, anti-B7-H4 antibodies, anti-BTLA antibodies, anti-IDO antibodies, anti-KIR antibodies, anti-LAG3 antibodies, anti-TIM3 antibodies and anti-VISTA (V-domain Ig suppressor of T cell activation) antibodies.

Anti-CTLA4 antibodies can include, but are not limited to, ipilimumab, tremelimumab and AGEN-1884. Anti-PD-1 antibodies include, but are not limited to, pembrolizumab, nivolumab pidilizumab, cemiplimab, REGN2810, AMP-224, MEDI0680, PDR001 and CT-001. Anti-PD-L1 antibodies include, but are not limited to atezolizumab, avelumab and durvalumab. Anti-CD137 antibodies include, but are not limited to, urelumab. Anti-B7-H3 antibodies include, but are not limited to, MGA271. Anti-KIR antibodies include, but are not limited to, Lirilumab. Anti-LAG3 antibodies include, but are not limited to, BMS-986016.

The term “immunotherapy” can refer to activating immunotherapy or suppressing immunotherapy. As will be appreciated by those in the art, activating immunotherapy refers to the use of a therapeutic agent that induces, enhances, or promotes an immune response, including, e.g., a T cell response while suppressing immunotherapy refers to the use of a therapeutic agent that interferes with, suppresses, or inhibits an immune response, including, e.g., a T cell response. Activating immunotherapy may comprise the use of checkpoint inhibitors. Activating immunotherapy may comprise administering to a subject a therapeutic agent that activates a stimulatory checkpoint molecule. Stimulatory checkpoint molecules include, but are not limited to, CD27, CD28, CD40, CD122, CD137, OX40, GITR and ICOS. Therapeutic agents that activate a stimulatory checkpoint molecule include, but are not limited to, MEDI0562, TGN1412, CDX-1127, lipocalin.

The term “antibody” herein is used in the broadest sense and encompasses various antibody structures, including but not limited to monoclonal antibodies, polyclonal antibodies, multispecific antibodies (e.g., bispecific antibodies), and antibody fragments so long as they exhibit the desired antigen-binding activity. An antibody that binds to a target refers to an antibody that is capable of binding the target with sufficient affinity such that the antibody is useful as a diagnostic and/or therapeutic agent in targeting the target. In one embodiment, the extent of binding of an anti-target antibody to an unrelated, non-target protein is less than about 10% of the binding of the antibody to target as measured, e.g., by a radioimmunoassay (MA) or biacore assay. In certain embodiments, an antibody that binds to a target has a dissociation constant (Kd) of <1 μM, <100 nM, <10 nM, <1 nM, <0.1 nM, <0.01 nM, or <0.001 nM (e.g. 10⁸ M or less, e.g. from 10⁸ M to 10¹³ M, e.g., from 10⁹ M to 10¹³ M). In certain embodiments, an anti-target antibody binds to an epitope of a target that is conserved among different species.

A “blocking antibody” or an “antagonist antibody” is one that partially or fully blocks, inhibits, interferes, or neutralizes a normal biological activity of the antigen it binds. For example, an antagonist antibody may block signaling through an immune cell receptor (e.g., a T cell receptor) so as to restore a functional response by T cells (e.g., proliferation, cytokine production, target cell killing) from a dysfunctional state to antigen stimulation.

An “agonist antibody” or “activating antibody” is one that mimics, promotes, stimulates, or enhances a normal biological activity of the antigen it binds. Agonist antibodies can also enhance or initiate signaling by the antigen to which it binds. In some embodiments, agonist antibodies cause or activate signaling without the presence of the natural ligand. For example, an agonist antibody may increase memory T cell proliferation, increase cytokine production by memory T cells, inhibit regulatory T cell function, and/or inhibit regulatory T cell suppression of effector T cell function, such as effector T cell proliferation and/or cytokine production.

An “antibody fragment” refers to a molecule other than an intact antibody that comprises a portion of an intact antibody that binds the antigen to which the intact antibody binds. Examples of antibody fragments include but are not limited to Fv, Fab, Fab′, Fab′-SH, F(ab′)2; diabodies; linear antibodies; single-chain antibody molecules (e.g. scFv); and multispecific antibodies formed from antibody fragments.

Administering chemotherapy to a subject can comprise administering a therapeutically effective dose of at least one chemotherapeutic agent. Chemotherapeutic agents include, but are not limited to, 13-cis-Retinoic Acid, 2-CdA, 2-Chlorodeoxyadenosine, 5-Azacitidine, 5-Fluorouracil, 5-FU, 6-Mercaptopurine, 6-MP, 6-TG, 6-Thioguanine, Abemaciclib, Abiraterone acetate, Abraxane, Accutane, Actinomycin-D, Adcetris, Ado-Trastuzumab Emtansine, Adriamycin, Adrucil, Afatinib, Afinitor, Agrylin, Ala-Cort, Aldesleukin, Alemtuzumab, Alecensa, Alectinib, Alimta, Alitretinoin, Alkaban-AQ, Alkeran, All-transretinoic Acid, Alpha Interferon, Altretamine, Alunbrig, Amethopterin, Amifostine, Aminoglutethimide, Anagrelide, Anandron, Anastrozole, Apalutamide, Arabinosylcytosine, Ara-C, Aranesp, Aredia, Arimidex, Aromasin, Arranon, Arsenic Trioxide, Arzerra, Asparaginase, Atezolizumab, Atra, Avastin, Avelumab, Axicabtagene Ciloleucel, Axitinib, Azacitidine, Bavencio, Bcg, Beleodaq, Belinostat, Bendamustine, Bendeka, Besponsa, Bevacizumab, Bexarotene, Bexxar, Bicalutamide, Bicnu, Blenoxane, Bleomycin, Blinatumomab, Blincyto, Bortezomib, Bosulif, Bosutinib, Brentuximab Vedotin, Brigatinib, Busulfan, Busulfex, C225, Cabazitaxel, Cabozantinib, Calcium Leucovorin, Campath, Camptosar, Camptothecin-11, Capecitabine, Caprelsa, Carac, Carboplatin, Carfilzomib, Carmustine, Carmustine Wafer, Casodex, CCI-779, Ccnu, Cddp, Ceenu, Ceritinib, Cerubidine, Cetuximab, Chlorambucil, Cisplatin, Citrovorum Factor, Cladribine, Clofarabine, Clolar, Cobimetinib, Cometriq, Cortisone, Cosmegen, Cotellic, Cpt-11, Crizotinib, Cyclophosphamide, Cyramza, Cytadren, Cytarabine, Cytarabine Liposomal, Cytosar-U, Cytoxan, Dabrafenib, Dacarbazine, Dacogen, Dactinomycin, Daratumumab, Darbepoetin Alfa, Darzalex, Dasatinib, Daunomycin, Daunorubicin, Daunorubicin Cytarabine (Liposomal), daunorubicin-hydrochloride, Daunorubicin Liposomal, DaunoXome, Decadron, Decitabine, Degarelix, Delta-Cortef, Deltasone, Denileukin Diftitox, Denosumab, DepoCyt, Dexamethasone, Dexamethasone Acetate, Dexamethasone Sodium Phosphate, Dexasone, Dexrazoxane, Dhad, Dic, Diodex, Docetaxel, Doxil, Doxorubicin, Doxorubicin Liposomal, Droxia, DTIC, Dtic-Dome, Duralone, Durvalumab, Eculizumab, Efudex, Ellence, Elotuzumab, Eloxatin, Elspar, Eltrombopag, Emcyt, Empliciti, Enasidenib, Enzalutamide, Epirubicin, Epoetin Alfa, Erbitux, Eribulin, Erivedge, Erleada, Erlotinib, Erwinia L-asparaginase, Estramustine, Ethyol, Etopophos, Etoposide, Etoposide Phosphate, Eulexin, Everolimus, Evista, Exemestane, Fareston, Farydak, Faslodex, Femara, Filgrastim, Firmagon, Floxuridine, Fludara, Fludarabine, Fluoroplex, Fluorouracil, Fluorouracil (cream), Fluoxymesterone, Flutamide, Folinic Acid, Folotyn, Fudr, Fulvestrant, G-Csf, Gazyva, Gefitinib, Gemcitabine, Gemtuzumab ozogamicin, Gemzar, Gilotrif, Gleevec, Gleostine, Gliadel Wafer, Gm-Csf, Goserelin, Granix, Granulocyte—Colony Stimulating Factor, Granulocyte Macrophage Colony Stimulating Factor, Halaven, Halotestin, Herceptin, Hexadrol, Hexalen, Hexamethylmelamine, Hmm, Hycamtin, Hydrea, Hydrocort Acetate, Hydrocortisone, Hydrocortisone Sodium Phosphate, Hydrocortisone Sodium Succinate, Hydrocortone Phosphate, Hydroxyurea, Ibrance, Ibritumomab, Ibritumomab Tiuxetan, Ibrutinib, Iclusig, Idamycin, Idarubicin, Idelalisib, Idhifa, Ifex, IFN-alpha, Ifosfamide, IL-11, IL-2, Imbruvica, Imatinib Mesylate, Imfinzi, Imidazole Carboxamide, Imlygic, Inlyta, Inotuzumab Ozogamicin, Interferon-Alfa, Interferon Alfa-2b (PEG Conjugate), Interleukin-2, Interleukin-11, Intron A (interferon alfa-2b), Ipilimumab, Iressa, Irinotecan, Irinotecan (Liposomal), Isotretinoin, Istodax, Ixabepilone, Ixazomib, Ixempra, Jakafi, Jevtana, Kadcyla, Keytruda, Kidrolase, Kisqali, Kymriah, Kyprolis, Lanacort, Lanreotide, Lapatinib, Lartruvo, L-Asparaginase, Lbrance, Lcr, Lenalidomide, Lenvatinib, Lenvima, Letrozole, Leucovorin, Leukeran, Leukine, Leuprolide, Leurocristine, Leustatin, Liposomal Ara-C, Liquid Pred, Lomustine, Lonsurf, L-PAM, L-Sarcolysin, Lupron, Lupron Depot, Lynparza, Marqibo, Matulane, Maxidex, Mechlorethamine, Mechlorethamine Hydrochloride, Medralone, Medrol, Megace, Megestrol, Megestrol Acetate, Mekinist, Mercaptopurine, Mesna, Mesnex, Methotrexate, Methotrexate Sodium, Methylprednisolone, Meticorten, Midostaurin, Mitomycin, Mitomycin-C, Mitoxantrone, M-Prednisol, MTC, MTX, Mustargen, Mustine, Mutamycin, Myleran, Mylocel, Mylotarg, Navelbine, Necitumumab, Nelarabine, Neosar, Neratinib, Nerlynx, Neulasta, Neumega, Neupogen, Nexavar, Nilandron, Nilotinib, Nilutamide, Ninlaro, Nipent, Niraparib, Nitrogen Mustard, Nivolumab, Nolvadex, Novantrone, Nplate, Obinutuzumab, Octreotide, Octreotide Acetate, Odomzo, Ofatumumab, Olaparib, Olaratumab, Omacetaxine, Oncospar, Oncovin, Onivyde, Ontak, Onxal, Opdivo, Oprelvekin, Orapred, Orasone, Osimertinib, Otrexup, Oxaliplatin, Paclitaxel, Paclitaxel Protein-bound, Palbociclib, Pamidronate, Panitumumab, Panobinostat, Panretin, Paraplatin, Pazopanib, Pediapred, Peg Interferon, Pegaspargase, Pegfilgrastim, Peg-Intron, PEG-L-asparaginase, Pembrolizumab, Pemetrexed, Pentostatin, Perjeta, Pertuzumab, Phenylalanine Mustard, Platinol, Platinol-AQ, Pomalidomide, Pomalyst, Ponatinib, Portrazza, Pralatrexate, Prednisolone, Prednisone, Prelone, Procarbazine, Procrit, Proleukin, Prolia, Prolifeprospan 20 with Carmustine Implant, Promacta, Provenge, Purinethol, Radium 223 Dichloride, Raloxifene, Ramucirumab, Rasuvo, Regorafenib, Revlimid, Rheumatrex, Ribociclib, Rituxan, Rituxan Hycela, Rituximab, Rituximab Hyalurodinase, Roferon-A (Interferon Alfa-2a), Romidepsin, Romiplostim, Rubex, Rubidomycin Hydrochloride, Rubraca, Rucaparib, Ruxolitinib, Rydapt, Sandostatin, Sandostatin LAR, Sargramostim, Siltuximab, Sipuleucel-T, Soliris, Solu-Cortef, Solu-Medrol, Somatuline, Sonidegib, Sorafenib, Sprycel, Sti-571, Stivarga, Streptozocin, SU11248, Sunitinib, Sutent, Sylvant, Synribo, Tafinlar, Tagrisso, Talimogene Laherparepvec, Tamoxifen, Tarceva, Targretin, Tasigna, Taxol, Taxotere, Tecentriq, Temodar, Temozolomide, Temsirolimus, Teniposide, Tespa, Thalidomide, Thalomid, TheraCys, Thioguanine, Thioguanine Tabloid, Thiophosphoamide, Thioplex, Thiotepa, Tice, Tisagenlecleucel, Toposar, Topotecan, Toremifene, Torisel, Tositumomab, Trabectedin, Trametinib, Trastuzumab, Treanda, Trelstar, Tretinoin, Trexall, Trifluridine/Tipiricil, Triptorelin pamoate, Trisenox, Tspa, T-VEC, Tykerb, Valrubicin, Valstar, Vandetanib, VCR, Vectibix, Velban, Velcade, Vemurafenib, Venclexta, Venetoclax, VePesid, Verzenio, Vesanoid, Viadur, Vidaza, Vinblastine, Vinblastine Sulfate, Vincasar Pfs, Vincristine, Vincristine Liposomal, Vinorelbine, Vinorelbine Tartrate, Vismodegib, Vlb, VM-26, Vorinostat, Votrient, VP-16, Vumon, Vyxeos, Xalkori Capsules, Xeloda, Xgeva, Xofigo, Xtandi, Yervoy, Yescarta, Yondelis, Zaltrap, Zanosar, Zarxio, Zejula, Zelboraf, Zevalin, Zinecard, Ziv-aflibercept, Zoladex, Zoledronic Acid, Zolinza, Zometa, Zydelig, Zykadia, Zytiga, or any combination thereof.

Table 1 details the biomarker/housekeeper sequence information. The amplicon positions identified for each biomarker are underlined.

TABLE 1 Gene RefSeq SEQ ID Name Accession Sequence NO: ARAF1 NM_001654.4 CTTGACAGACGTGACCCTGACCCAATAAGGGTGGAAGGCTGAGTCC  1 CGCAGAGCCAATAACGAGAGTCCGAGAGGCGACGGAGGCGGACTCT GTGAGGAAACAAGAAGAGAGGCCCAAGATGGAGACGGCGGCGGCTG TAGCGGCGTGACAGGAGCCCCATGGCACCTGCCCAGCCCCACCTCA GCCCATCTTGACAAAATCTAAGGCTCCATGGAGCCACCACGGGGCC CCCCTGCCAATGGGGCCGAGCCATCCCGGGCAGTGGGCACCGTCAA AGTATACCTGCCCAACAAGCAACGCACGGTGGTGACTGTCCGGGAT GGCATGAGTGTCTACGACTCTCTAGACAAGGCCCTGAAGGTGCGGG GTCTAAATCAGGACTGCTGTGTGGTCTACCGACTCATCAAGGGACG AAAGACGGTCACTGCCTGGGACACAGCCATTGCTCCCCTGGATGGC GAGGAGCTCATTGTCGAGGTCCTTGAAGATGTCCCGCTGACCATGC ACAATTTTGTACGGAAGACCTTCTTCAGCCTGGCGTTCTGTGACTT CTGCCTTAAGTTTCTGTTCCATGGCTTCCGTTGCCAAACCTGTGGC TACAAGTTCCACCAGCATTGTTCCTCCAAGGTCCCCACAGTCTGTG TTGACATGAGTACCAACCGCCAACAGTTCTACCACAGTGTCCAGGA TTTGTCCGGAGGCTCCAGACAGCATGAGGCTCCCTCGAACCGCCCC CTGAATGAGTTGCTAACCCCCCAGGGTCCCAGCCCCCGCACCCAGC ACTGTGACCCGGAGCACTTCCCCTTCCCTGCCCCAGCCAATGCCCC CCTACAGCGCATCCGCTCCACGTCCACTCCCAACGTCCATATGGTC AGCACCACGGCCCCCATGGACTCCAACCTCATCCAGCTCACTGGCC AGAGTTTCAGCACTGATGCTGCCGGTAGTAGAGGAGGTAGTGATGG AACCCCCCGGGGGAGCCCCAGCCCAGCCAGCGTGTCCTCGGGGAGG AAGTCCCCACATTCCAAGTCACCAGCAGAGCAGCGCGAGCGGAAGT CCTTGGCCGATGACAAGAAGAAAGTGAAGAACCTGGGGTACCGGGA CTCAGGCTATTACTGGGAGGTACCACCCAGTGAGGTGCAGCTGCTG AAGAGGATCGGGACGGGCTCGTTTGGCACCGTGTTTCGAGGGCGGT GGCATGGCGATGTGGCCGTGAAGGTGCTCAAGGTGTCCCAGCCCAC AGCTGAGCAGGCCCAGGCTTTCAAGAATGAGATGCAGGTGCTCAGG AAGACGCGACATGTCAACATCTTGCTGTTTATGGGCTTCATGACCC GGCCGGGATTTGCCATCATCACACAGTGGTGTGAGGGCTCCAGCCT CTACCATCACCTGCATGTGGCCGACACACGCTTCGACATGGTCCAG CTCATCGACGTGGCCCGGCAGACTGCCCAGGGCATGGACTACCTCC ATGCCAAGAACATCATCCACCGAGATCTCAAGTCTAACAACATCTT CCTACATGAGGGGCTCACGGTGAAGATCGGTGACTTTGGCTTGGCC ACAGTGAAGACTCGATGGAGCGGGGCCCAGCCCTTGGAGCAGCCCT CAGGATCTGTGCTGTGGATGGCAGCTGAGGTGATCCGTATGCAGGA CCCGAACCCCTACAGCTTCCAGTCAGACGTCTATGCCTACGGGGTT GTGCTCTACGAGCTTATGACTGGCTCACTGCCTTACAGCCACATTG GCTGCCGTGACCAGATTATCTTTATGGTGGGCCGTGGCTATCTGTC CCCGGACCTCAGCAAAATCTCCAGCAACTGCCCCAAGGCCATGCGG CGCCTGCTGTCTGACTGCCTCAAGTTCCAGCGGGAGGAGCGGCCCC TCTTCCCCCAGATCCTGGCCACAATTGAGCTGCTGCAACGGTCACT CCCCAAGATTGAGCGGAGTGCCTCGGAACCCTCCTTGCACCGCACC CAGGCCGATGAGTTGCCTGCCTGCCTACTCAGCGCAGCCCGCCTTG TGCCTTAGGCCCCGCCCAAGCCACCAGGGAGCCAATCTCAGCCCTC CACGCCAAGGAGCCTTGCCCACCAGCCAATCAATGTTCGTCTCTGC CCTGATGCTGCCTCAGGATCCCCCATTCCCCACCCTGGGAGATGAG GGGGTCCCCATGTGCTTTTCCAGTTCTTCTGGAATTGGGGGACCCC CGCCAAAGACTGAGCCCCCTGTCTCCTCCATCATTTGGTTTCCTCT TGGCTTTGGGGATACTTCTAAATTTTGGGAGCTCCTCCATCTCCAA TGGCTGGGATTTGTGGCAGGGATTCCACTCAGAACCTCTCTGGAAT TTGTGCCTGATGTGCCTTCCACTGGATTTTGGGGTTCCCAGCACCC CATGTGGATTTTGGGGGGTCCCTTTTGTGTCTCCCCCGCCATTCAA GGACTCCTCTCTTTCTTCACCAAGAAGCACAGAATTCTGCTGGGCC TTTGCTTGTTTAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA BRAF NM_004333.4 CGCCTCCCTTCCCCCTCCCCGCCCGACAGCGGCCGCTCGGGCCCCG  2 GCTCTCGGTTATAAGATGGCGGCGCTGAGCGGTGGCGGTGGTGGCG GCGCGGAGCCGGGCCAGGCTCTGTTCAACGGGGACATGGAGCCCGA GGCCGGCGCCGGCGCCGGCGCCGCGGCCTCTTCGGCTGCGGACCCT GCCATTCCGGAGGAGGTGTGGAATATCAAACAAATGATTAAGTTGA CACAGGAACATATAGAGGCCCTATTGGACAAATTTGGTGGGGAGCA TAATCCACCATCAATATATCTGGAGGCCTATGAAGAATACACCAGC AAGCTAGATGCACTCCAACAAAGAGAACAACAGTTATTGGAATCTC TGGGGAACGGAACTGATTTTTCTGTTTCTAGCTCTGCATCAATGGA TACCGTTACATCTTCTTCCTCTTCTAGCCTTTCAGTGCTACCTTCA TCTCTTTCAGTTTTTCAAAATCCCACAGATGTGGCACGGAGCAACC CCAAGTCACCACAAAAACCTATCGTTAGAGTCTTCCTGCCCAACAA ACAGAGGACAGTGGTACCTGCAAGGTGTGGAGTTACAGTCCGAGAC AGTCTAAAGAAAGCACTGATGATGAGAGGTCTAATCCCAGAGTGCT GTGCTGTTTACAGAATTCAGGATGGAGAGAAGAAACCAATTGGTTG GGACACTGATATTTCCTGGCTTACTGGAGAAGAATTGCATGTGGAA GTGTTGGAGAATGTTCCACTTACAACACACAACTTTGTACGAAAAA CGTTTTTCACCTTAGCATTTTGTGACTTTTGTCGAAAGCTGCTTTT CCAGGGTTTCCGCTGTCAAACATGTGGTTATAAATTTCACCAGCGT TGTAGTACAGAAGTTCCACTGATGTGTGTTAATTATGACCAACTTG ATTTGCTGTTTGTCTCCAAGTTCTTTGAACACCACCCAATACCACA GGAAGAGGCGTCCTTAGCAGAGACTGCCCTAACATCTGGATCATCC CCTTCCGCACCCGCCTCGGACTCTATTGGGCCCCAAATTCTCACCA GTCCGTCTCCTTCAAAATCCATTCCAATTCCACAGCCCTTCCGACC AGCAGATGAAGATCATCGAAATCAATTTGGGCAACGAGACCGATCC TCATCAGCTCCCAATGTGCATATAAACACAATAGAACCTGTCAATA TTGATGACTTGATTAGAGACCAAGGATTTCGTGGTGATGGAGGATC AACCACAGGTTTGTCTGCTACCCCCCCTGCCTCATTACCTGGCTCA CTAACTAACGTGAAAGCCTTACAGAAATCTCCAGGACCTCAGCGAG AAAGGAAGTCATCTTCATCCTCAGAAGACAGGAATCGAATGAAAAC ACTTGGTAGACGGGACTCGAGTGATGATTGGGAGATTCCTGATGGG CAGATTACAGTGGGACAAAGAATTGGATCTGGATCATTTGGAACAG TCTACAAGGGAAAGTGGCATGGTGATGTGGCAGTGAAAATGTTGAA TGTGACAGCACCTACACCTCAGCAGTTACAAGCCTTCAAAAATGAA GTAGGAGTACTCAGGAAAACACGACATGTGAATATCCTACTCTTCA TGGGCTATTCCACAAAGCCACAACTGGCTATTGTTACCCAGTGGTG TGAGGGCTCCAGCTTGTATCACCATCTCCATATCATTGAGACCAAA TTTGAGATGATCAAACTTATAGATATTGCACGACAGACTGCACAGG GCATGGATTACTTACACGCCAAGTCAATCATCCACAGAGACCTCAA GAGTAATAATATATTTCTTCATGAAGACCTCACAGTAAAAATAGGT GATTTTGGTCTAGCTACAGTGAAATCTCGATGGAGTGGGTCCCATC AGTTTGAACAGTTGTCTGGATCCATTTTGTGGATGGCACCAGAAGT CATCAGAATGCAAGATAAAAATCCATACAGCTTTCAGTCAGATGTA TATGCATTTGGAATTGTTCTGTATGAATTGATGACTGGACAGTTAC CTTATTCAAACATCAACAACAGGGACCAGATAATTTTTATGGTGGG ACGAGGATACCTGTCTCCAGATCTCAGTAAGGTACGGAGTAACTGT CCAAAAGCCATGAAGAGATTAATGGCAGAGTGCCTCAAAAAGAAAA GAGATGAGAGACCACTCTTTCCCCAAATTCTCGCCTCTATTGAGCT GCTGGCCCGCTCATTGCCAAAAATTCACCGCAGTGCATCAGAACCC TCCTTGAATCGGGCTGGTTTCCAAACAGAGGATTTTAGTCTATATG CTTGTGCTTCTCCAAAAACACCCATCCAGGCAGGGGGATATGGTGC GTTTCCTGTCCACTGAAACAAATGAGTGAGAGAGTTCAGGAGAGTA GCAACAAAAGGAAAATAAATGAACATATGTTTGCTTATATGTTAAA TTGAATAAAATACTCTCTTTTTTTTTAAGGTGAACCAAAGAACACT TGTGTGGTTAAAGACTAGATATAATTTTTCCCCAAACTAAAATTTA TACTTAACATTGGATTTTTAACATCCAAGGGTTAAAATACATAGAC ATTGCTAAAAATTGGCAGAGCCTCTTCTAGAGGCTTTACTTTCTGT TCCGGGTTTGTATCATTCACTTGGTTATTTTAAGTAGTAAACTTCA GTTTCTCATGCAACTTTTGTTGCCAGCTATCACATGTCCACTAGGG ACTCCAGAAGAAGACCCTACCTATGCCTGTGTTTGCAGGTGAGAAG TTGGCAGTCGGTTAGCCTGGGTTAGATAAGGCAAACTGAACAGATC TAATTTAGGAAGTCAGTAGAATTTAATAATTCTATTATTATTCTTA ATAATTTTTCTATAACTATTTCTTTTTATAACAATTTGGAAAATGT GGATGTCTTTTATTTCCTTGAAGCAATAAACTAAGTTTCTTTTTAT AAAAA KRAS NM_004985.4 TCCTAGGCGGCGGCCGCGGCGGCGGAGGCAGCAGCGGCGGCGGCAG  3 TGGCGGCGGCGAAGGTGGCGGCGGCTCGGCCAGTACTCCCGGCCCC CGCCATTTCGGACTGGGAGCGAGCGCGGCGCAGGCACTGAAGGCGG CGGCGGGGCCAGAGGCTCAGCGGCTCCCAGGTGCGGGAGAGAGGCC TGCTGAAAATGACTGAATATAAACTTGTGGTAGTTGGAGCTGGTGG CGTAGGCAAGAGTGCCTTGACGATACAGCTAATTCAGAATCATTTT GTGGACGAATATGATCCAACAATAGAGGATTCCTACAGGAAGCAAG TAGTAATTGATGGAGAAACCTGTCTCTTGGATATTCTCGACACAGC AGGTCAAGAGGAGTACAGTGCAATGAGGGACCAGTACATGAGGACT GGGGAGGGCTTTCTTTGTGTATTTGCCATAAATAATACTAAATCAT TTGAAGATATTCACCATTATAGAGAACAAATTAAAAGAGTTAAGGA CTCTGAAGATGTACCTATGGTCCTAGTAGGAAATAAATGTGATTTG CCTTCTAGAACAGTAGACACAAAACAGGCTCAGGACTTAGCAAGAA GTTATGGAATTCCTTTTATTGAAACATCAGCAAAGACAAGACAGGG TGTTGATGATGCCTTCTATACATTAGTTCGAGAAATTCGAAAACAT AAAGAAAAGATGAGCAAAGATGGTAAAAAGAAGAAAAAGAAGTCAA AGACAAAGTGTGTAATTATGTAAATACAATTTGTACTTTTTTCTTA AGGCATACTAGTACAAGTGGTAATTTTTGTACATTACACTAAATTA TTAGCATTTGTTTTAGCATTACCTAATTTTTTTCCTGCTCCATGCA GACTGTTAGCTTTTACCTTAAATGCTTATTTTAAAATGACAGTGGA AGTTTTTTTTTCCTCTAAGTGCCAGTATTCCCAGAGTTTTGGTTTT TGAACTAGCAATGCCTGTGAAAAAGAAACTGAATACCTAAGATTTC TGTCTTGGGGTTTTTGGTGCATGCAGTTGATTACTTCTTATTTTTC TTACCAATTGTGAATGTTGGTGTGAAACAAATTAATGAAGCTTTTG AATCATCCCTATTCTGTGTTTTATCTAGTCACATAAATGGATTAAT TACTAATTTCAGTTGAGACCTTCTAATTGGTTTTTACTGAAACATT GAGGGAACACAAATTTATGGGCTTCCTGATGATGATTCTTCTAGGC ATCATGTCCTATAGTTTGTCATCCCTGATGAATGTAAAGTTACACT GTTCACAAAGGTTTTGTCTCCTTTCCACTGCTATTAGTCATGGTCA CTCTCCCCAAAATATTATATTTTTTCTATAAAAAGAAAAAAATGGA AAAAAATTACAAGGCAATGGAAACTATTATAAGGCCATTTCCTTTT CACATTAGATAAATTACTATAAAGACTCCTAATAGCTTTTCCTGTT AAGGCAGACCCAGTATGAAATGGGGATTATTATAGCAACCATTTTG GGGCTATATTTACATGCTACTAAATTTTTATAATAATTGAAAAGAT TTTAACAAGTATAAAAAATTCTCATAGGAATTAAATGTAGTCTCCC TGTGTCAGACTGCTCTTTCATAGTATAACTTTAAATCTTTTCTTCA ACTTGAGTCTTTGAAGATAGTTTTAATTCTGCTTGTGACATTAAAA GATTATTTGGGCCAGTTATAGCTTATTAGGTGTTGAAGAGACCAAG GTTGCAAGGCCAGGCCCTGTGTGAACCTTTGAGCTTTCATAGAGAG TTTCACAGCATGGACTGTGTCCCCACGGTCATCCAGTGTTGTCATG CATTGGTTAGTCAAAATGGGGAGGGACTAGGGCAGTTTGGATAGCT CAACAAGATACAATCTCACTCTGTGGTGGTCCTGCTGACAAATCAA GAGCATTGCTTTTGTTTCTTAAGAAAACAAACTCTTTTTTAAAAAT TACTTTTAAATATTAACTCAAAAGTTGAGATTTTGGGGTGGTGGTG TGCCAAGACATTAATTTTTTTTTTAAACAATGAAGTGAAAAAGTTT TACAATCTCTAGGTTTGGCTAGTTCTCTTAACACTGGTTAAATTAA CATTGCATAAACACTTTTCAAGTCTGATCCATATTTAATAATGCTT TAAAATAAAAATAAAAACAATCCTTTTGATAAATTTAAAATGTTAC TTATTTTAAAATAAATGAAGTGAGATGGCATGGTGAGGTGAAAGTA TCACTGGACTAGGAAGAAGGTGACTTAGGTTCTAGATAGGTGTCTT TTAGGACTCTGATTTTGAGGACATCACTTACTATCCATTTCTTCAT GTTAAAAGAAGTCATCTCAAACTCTTAGTTTTTTTTTTTTACAACT ATGTAATTTATATTCCATTTACATAAGGATACACTTATTTGTCAAG CTCAGCACAATCTGTAAATTTTTAACCTATGTTACACCATCTTCAG TGCCAGTCTTGGGCAAAATTGTGCAAGAGGTGAAGTTTATATTTGA ATATCCATTCTCGTTTTAGGACTCTTCTTCCATATTAGTGTCATCT TGCCTCCCTACCTTCCACATGCCCCATGACTTGATGCAGTTTTAAT ACTTGTAATTCCCCTAACCATAAGATTTACTGCTGCTGTGGATATC TCCATGAAGTTTTCCCACTGAGTCACATCAGAAATGCCCTACATCT TATTTCCTCAGGGCTCAAGAGAATCTGACAGATACCATAAAGGGAT TTGACCTAATCACTAATTTTCAGGTGGTGGCTGATGCTTTGAACAT CTCTTTGCTGCCCAATCCATTAGCGACAGTAGGATTTTTCAAACCT GGTATGAATAGACAGAACCCTATCCAGTGGAAGGAGAATTTAATAA AGATAGTGCTGAAAGAATTCCTTAGGTAATCTATAACTAGGACTAC TCCTGGTAACAGTAATACATTCCATTGTTTTAGTAACCAGAAATCT TCATGCAATGAAAAATACTTTAATTCATGAAGCTTACTTTTTTTTT TTGGTGTCAGAGTCTCGCTCTTGTCACCCAGGCTGGAATGCAGTGG CGCCATCTCAGCTCACTGCAACCTCCATCTCCCAGGTTCAAGCGAT TCTCGTGCCTCGGCCTCCTGAGTAGCTGGGATTACAGGCGTGTGCC ACTACACTCAACTAATTTTTGTATTTTTAGGAGAGACGGGGTTTCA CCCTGTTGGCCAGGCTGGTCTCGAACTCCTGACCTCAAGTGATTCA CCCACCTTGGCCTCATAAACCTGTTTTGCAGAACTCATTTATTCAG CAAATATTTATTGAGTGCCTACCAGATGCCAGTCACCGCACAAGGC ACTGGGTATATGGTATCCCCAAACAAGAGACATAATCCCGGTCCTT AGGTAGTGCTAGTGTGGTCTGTAATATCTTACTAAGGCCTTTGGTA TACGACCCAGAGATAACACGATGCGTATTTTAGTTTTGCAAAGAAG GGGTTTGGTCTCTGTGCCAGCTCTATAATTGTTTTGCTACGATTCC ACTGAAACTCTTCGATCAAGCTACTTTATGTAAATCACTTCATTGT TTTAAAGGAATAAACTTGATTATATTGTTTTTTTATTTGGCATAAC TGTGATTCTTTTAGGACAATTACTGTACACATTAAGGTGTATGTCA GATATTCATATTGACCCAAATGTGTAATATTCCAGTTTTCTCTGCA TAAGTAATTAAAATATACTTAAAAATTAATAGTTTTATCTGGGTAC AAATAAACAGGTGCCTGAACTAGTTCACAGACAAGGAAACTTCTAT GTAAAAATCACTATGATTTCTGAATTGCTATGTGAAACTACAGATC TTTGGAACACTGTTTAGGTAGGGTGTTAAGACTTACACAGTACCTC GTTTCTACACAGAGAAAGAAATGGCCATACTTCAGGAACTGCAGTG CTTATGAGGGGATATTTAGGCCTCTTGAATTTTTGATGTAGATGGG CATTTTTTTAAGGTAGTGGTTAATTACCTTTATGTGAACTTTGAAT GGTTTAACAAAAGATTTGTTTTTGTAGAGATTTTAAAGGGGGAGAA TTCTAGAAATAAATGTTACCTAATTATTACAGCCTTAAAGACAAAA ATCCTTGTTGAAGTTTTTTTAAAAAAAGCTAAATTACATAGACTTA GGCATTAACATGTTTGTGGAAGAATATAGCAGACGTATATTGTATC ATTTGAGTGAATGTTCCCAAGTAGGCATTCTAGGCTCTATTTAACT GAGTCACACTGCATAGGAATTTAGAACCTAACTTTTATAGGTTATC AAAACTGTTGTCACCATTGCACAATTTTGTCCTAATATATACATAG AAACTTTGTGGGGCATGTTAAGTTACAGTTTGCACAAGTTCATCTC ATTTGTATTCCATTGATTTTTTTTTTCTTCTAAACATTTTTTCTTC AAACAGTATATAACTTTTTTTAGGGGATTTTTTTTTAGACAGCAAA AACTATCTGAAGATTTCCATTTGTCAAAAAGTAATGATTTCTTGAT AATTGTGTAGTAATGTTTTTTAGAACCCAGCAGTTACCTTAAAGCT GAATTTATATTTAGTAACTTCTGTGTTAATACTGGATAGCATGAAT TCTGCATTGAGAAACTGAATAGCTGTCATAAAATGAAACTTTCTTT CTAAAGAAAGATACTCACATGAGTTCTTGAAGAATAGTCATAACTA GATTAAGATCTGTGTTTTAGTTTAATAGTTTGAAGTGCCTGTTTGG GATAATGATAGGTAATTTAGATGAATTTAGGGGAAAAAAAAGTTAT CTGCAGATATGTTGAGGGCCCATCTCTCCCCCCACACCCCCACAGA GCTAACTGGGTTACAGTGTTTTATCCGAAAGTTTCCAATTCCACTG TCTTGTGTTTTCATGTTGAAAATACTTTTGCATTTTTCCTTTGAGT GCCAATTTCTTACTAGTACTATTTCTTAATGTAACATGTTTACCTG GAATGTATTTTAACTATTTTTGTATAGTGTAAACTGAAACATGCAC ATTTTGTACATTGTGCTTTCTTTTGTGGGACATATGCAGTGTGATC CAGTTGTTTTCCATCATTTGGTTGCGCTGACCTAGGAATGTTGGTC ATATCAAACATTAAAAATGACCACTCTTTTAATTGAAATTAACTTT TAAATGTTTATAGGAGTATGTGCTGTGAAGTGATCTAAAATTTGTA ATATTTTTGTCATGAACTGTACTACTCCTAATTATTGTAATGTAAT AAAAATAGTTACAGTGACTATGAGTGTGTATTTATTCATGAAATTT GAACTGTTTGCCCCGAAATGGATATGGAATACTTTATAAGCCATAG ACACTATAGTATACCAGTGAATCTTTTATGCAGCTTGTTAGAAGTA TCCTTTATTTCTAAAAGGTGCTGTGGATATTATGTAAAGGCGTGTT TGCTTAAACTTAAAACCATATTTAGAAGTAGATGCAAAACAAATCT GCCTTTATGACAAAAAAATAGGATAACATTATTTATTTATTTCCTT TTATCAAAGAAGGTAATTGATACACAACAGGTGACTTGGTTTTAGG CCCAAAGGTAGCAGCAGCAACATTAATAATGGAAATAATTGAATAG TTAGTTATGTATGTTAATGCCAGTCACCAGCAGGCTATTTCAAGGT CAGAAGTAATGACTCCATACATATTATTTATTTCTATAACTACATT TAAATCATTACCAGG RAF-1 NM_002880.3 AGAATCGGAGAGCCGGTGGCGTCGCAGGTCGGGAGGACGAGCACCG  4 AGTCGAGGGCTCGCTCGTCTGGGCCGCCCGAGAGTCTTAATCGCGG GCGCTTGGGCCGCCATCTTAGATGGCGGGAGTAAGAGGAAAACGAT TGTGAGGCGGGAACGGCTTTCTGCTGCCTTTTTTGGGCCCCGAAAA GGGTCAGCTGGCCGGGCTTTGGGGCGCGTGCCCTGAGGCGCGGAGC GCGTTTGCTACGATGCGGGGGCTGCTCGGGGCTCCGTCCCCTGGGC TGGGGACGCGCCGAATGTGACCGCCTCCCGCTCCCTCACCCGCCGC GGGGAGGAGGAGCGGGCGAGAAGCTGCCGCCGAACGACAGGACGTT GGGGCGGCCTGGCTCCCTCAGGTTTAAGAATTGTTTAAGCTGCATC AATGGAGCACATACAGGGAGCTTGGAAGACGATCAGCAATGGTTTT GGATTCAAAGATGCCGTGTTTGATGGCTCCAGCTGCATCTCTCCTA CAATAGTTCAGCAGTTTGGCTATCAGCGCCGGGCATCAGATGATGG CAAACTCACAGATCCTTCTAAGACAAGCAACACTATCCGTGTTTTC TTGCCGAACAAGCAAAGAACAGTGGTCAATGTGCGAAATGGAATGA GCTTGCATGACTGCCTTATGAAAGCACTCAAGGTGAGGGGCCTGCA ACCAGAGTGCTGTGCAGTGTTCAGACTTCTCCACGAACACAAAGGT AAAAAAGCACGCTTAGATTGGAATACTGATGCTGCGTCTTTGATTG GAGAAGAACTTCAAGTAGATTTCCTGGATCATGTTCCCCTCACAAC ACACAACTTTGCTCGGAAGACGTTCCTGAAGCTTGCCTTCTGTGAC ATCTGTCAGAAATTCCTGCTCAATGGATTTCGATGTCAGACTTGTG GCTACAAATTTCATGAGCACTGTAGCACCAAAGTACCTACTATGTG TGTGGACTGGAGTAACATCAGACAACTCTTATTGTTTCCAAATTCC ACTATTGGTGATAGTGGAGTCCCAGCACTACCTTCTTTGACTATGC GTCGTATGCGAGAGTCTGTTTCCAGGATGCCTGTTAGTTCTCAGCA CAGATATTCTACACCTCACGCCTTCACCTTTAACACCTCCAGTCCC TCATCTGAAGGTTCCCTCTCCCAGAGGCAGAGGTCGACATCCACAC CTAATGTCCACATGGTCAGCACCACCCTGCCTGTGGACAGCAGGAT GATTGAGGATGCAATTCGAAGTCACAGCGAATCAGCCTCACCTTCA GCCCTGTCCAGTAGCCCCAACAATCTGAGCCCAACAGGCTGGTCAC AGCCGAAAACCCCCGTGCCAGCACAAAGAGAGCGGGCACCAGTATC TGGGACCCAGGAGAAAAACAAAATTAGGCCTCGTGGACAGAGAGAT TCAAGCTATTATTGGGAAATAGAAGCCAGTGAAGTGATGCTGTCCA CTCGGATTGGGTCAGGCTCTTTTGGAACTGTTTATAAGGGTAAATG GCACGGAGATGTTGCAGTAAAGATCCTAAAGGTTGTCGACCCAACC CCAGAGCAATTCCAGGCCTTCAGGAATGAGGTGGCTGTTCTGCGCA AAACACGGCATGTGAACATTCTGCTTTTCATGGGGTACATGACAAA GGACAACCTGGCAATTGTGACCCAGTGGTGCGAGGGCAGCAGCCTC TACAAACACCTGCATGTCCAGGAGACCAAGTTTCAGATGTTCCAGC TAATTGACATTGCCCGGCAGACGGCTCAGGGAATGGACTATTTGCA TGCAAAGAACATCATCCATAGAGACATGAAATCCAACAATATATTT CTCCATGAAGGCTTAACAGTGAAAATTGGAGATTTTGGTTTGGCAA CAGTAAAGTCACGCTGGAGTGGTTCTCAGCAGGTTGAACAACCTAC TGGCTCTGTCCTCTGGATGGCCCCAGAGGTGATCCGAATGCAGGAT AACAACCCATTCAGTTTCCAGTCGGATGTCTACTCCTATGGCATCG TATTGTATGAACTGATGACGGGGGAGCTTCCTTATTCTCACATCAA CAACCGAGATCAGATCATCTTCATGGTGGGCCGAGGATATGCCTCC CCAGATCTTAGTAAGCTATATAAGAACTGCCCCAAAGCAATGAAGA GGCTGGTAGCTGACTGTGTGAAGAAAGTAAAGGAAGAGAGGCCTCT TTTTCCCCAGATCCTGTCTTCCATTGAGCTGCTCCAACACTCTCTA CCGAAGATCAACCGGAGCGCTTCCGAGCCATCCTTGCATCGGGCAG CCCACACTGAGGATATCAATGCTTGCACGCTGACCACGTCCCCGAG GCTGCCTGTCTTCTAGTTGACTTTGCACCTGTCTTCAGGCTGCCAG GGGAGGAGGAGAAGCCAGCAGGCACCACTTTTCTGCTCCCTTTCTC CAGAGGCAGAACACATGTTTTCAGAGAAGCTGCTGCTAAGGACCTT CTAGACTGCTCACAGGGCCTTAACTTCATGTTGCCTTCTTTTCTAT CCCTTTGGGCCCTGGGAGAAGGAAGCCATTTGCAGTGCTGGTGTGT CCTGCTCCCTCCCCACATTCCCCATGCTCAAGGCCCAGCCTTCTGT AGATGCGCAAGTGGATGTTGATGGTAGTACAAAAAGCAGGGGCCCA GCCCCAGCTGTTGGCTACATGAGTATTTAGAGGAAGTAAGGTAGCA GGCAGTCCAGCCCTGATGTGGAGACACATGGGATTTTGGAAATCAG CTTCTGGAGGAATGCATGTCACAGGCGGGACTTTCTTCAGAGAGTG GTGCAGCGCCAGACATTTTGCACATAAGGCACCAAACAGCCCAGGA CTGCCGAGACTCTGGCCGCCCGAAGGAGCCTGCTTTGGTACTATGG AACTTTTCTTAGGGGACACGTCCTCCTTTCACAGCTTCTAAGGTGT CCAGTGCATTGGGATGGTTTTCCAGGCAAGGCACTCGGCCAATCCG CATCTCAGCCCTCTCAGGGAGCAGTCTTCCATCATGCTGAATTTTG TCTTCCAGGAGCTGCCCCTATGGGGCGGGGCCGCAGGGCCAGCCTT GTTTCTCTAACAAACAAACAAACAAACAGCCTTGTTTCTCTAGTCA CATCATGTGTATACAAGGAAGCCAGGAATACAGGTTTTCTTGATGA TTTGGGTTTTAATTTTGTTTTTATTGCACCTGACAAAATACAGTTA TCTGATGGTCCCTCAATTATGTTATTTTAATAAAATAAATTAAATT GTAAAAAAAAAAAAAAAAAAAAAAA ATP6V1H NM_015941.3 AGCAGTCACGTGCCTCCGATCACGTGACCGGCGCCTCTGTCATTCT  5 ACTGCGGCCGCCCTGGCTTCCTTCTACCTGTGCGGCCCTCAACGTC TCCTTGGTGCGGGACCCGCTTCACTTTCGGCTCCCGGAGTCTCCCT CCACTGCTCAGACCTCTGGACCTGACAGGAGACGCCTACTTGGCTC TGACGCGGCGCCCCAGCCCGGCTGTGTCCCCGGCGCCCCGGACCAC CCTCCCTGCCGGCTTTGGGTGCGTTGTGGGGTCCCGAGGATTCGCG AGATTTGTTGAAAGACATTCAAGATTACGAAGTTTAGATGACCAAA ATGGATATCCGAGGTGCTGTGGATGCTGCTGTCCCCACCAATATTA TTGCTGCCAAGGCTGCAGAAGTTCGTGCAAACAAAGTCAACTGGCA ATCCTATCTTCAGGGACAGATGATTTCTGCTGAAGATTGTGAGTTT ATTCAGAGGTTTGAAATGAAACGAAGCCCTGAAGAGAAGCAAGAGA TGCTTCAAACTGAAGGCAGCCAGTGTGCTAAAACATTTATAAATCT GATGACTCATATCTGCAAAGAACAGACCGTTCAGTATATACTAACT ATGGTGGATGATATGCTGCAGGAAAATCATCAGCGTGTTAGCATTT TCTTTGACTATGCAAGATGTAGCAAGAACACTGCGTGGCCCTACTT TCTGCCAATGTTGAATCGCCAGGATCCCTTCACTGTTCATATGGCA GCAAGAATTATTGCCAAGTTAGCAGCTTGGGGAAAAGAACTGATGG AAGGCAGTGACTTAAATTACTATTTCAATTGGATAAAAACTCAGCT GAGTTCACAGAAACTGCGTGGTAGCGGTGTTGCTGTTGAAACAGGA ACAGTCTCTTCAAGTGATAGTTCGCAGTATGTGCAGTGCGTGGCCG GGTGTTTGCAGCTGATGCTCCGGGTCAATGAGTACCGCTTTGCTTG GGTGGAAGCAGATGGGGTAAATTGCATAATGGGAGTGTTGAGTAAC AAGTGTGGCTTTCAGCTCCAGTATCAAATGATTTTTTCAATATGGC TCCTGGCATTCAGTCCTCAAATGTGTGAACACCTGCGGCGCTATAA TATCATTCCAGTTCTGTCTGATATCCTTCAGGAGTCTGTCAAAGAG AAAGTAACAAGAATCATTCTTGCAGCATTTCGTAACTTTTTAGAAA AATCAACTGAAAGAGAAACTCGCCAAGAATATGCCCTGGCTATGAT TCAGTGCAAAGTTCTGAAACAGTTGGAGAACTTGGAACAGCAGAAG TACGATGATGAAGATATCAGCGAAGATATCAAATTTCTTTTGGAAA AACTTGGAGAGAGTGTCCAGGACCTTAGTTCATTTGATGAATACAG TTCAGAACTTAAATCTGGAAGGTTGGAATGGAGTCCTGTGCACAAA TCTGAGAAATTTTGGAGAGAGAATGCTGTGAGGTTAAATGAGAAGA ATTATGAACTCTTGAAAATCTTGACAAAACTTTTGGAAGTGTCAGA TGATCCCCAAGTCTTAGCTGTTGCTGCTCACGATGTTGGAGAATAT GTGCGGCATTATCCACGAGGCAAACGGGTCATCGAGCAGCTCGGTG GGAAGCAGCTGGTCATGAACCACATGCATCATGAAGACCAGCAGGT CCGCTATAATGCTCTGCTGGCCGTGCAGAAGCTCATGGTGCACAAC TGGGAATACCTTGGCAAGCAGCTCCAGTCCGAGCAGCCCCAGACCG CTGCCGCCCGAAGCTAAGCCTGCCTCTGGCCTTCCCCTCCGCCTCA ATGCAGAACCAGTAGTGGGAGCACTGTGTTTAGAGTTAAGAGTGAA CACTGTTTGATTTTACTTGGAATTTCCTCTGTTATATAGCTTTTCC CAATGCTAATTTCCAAACAACAACAACAAAATAACATGTTTGCCTG TTAAGTTGTATAAAAGTAGGTGATTCTGTATTTAAAGAAAATATTA CTGTTACATATACTGCTTGCAATTTCTGTATTTATTGTTCTCTGGA AATAAATATAGTTATTAAAGGATTCTCACTCCAAACATGGCCTCTC TCTTTACTTGGACTTTGAACAAAAGTCAACTGTTGTCTCTTTTCAA ACCAAATTGGGAGAATTGTTGCAAAGTAGTGAATGGCAAATAAATG TTTTAAAATCTATCGCTCTATCAA OAZ2 NM_002537.3 ATGCAGATGAGGCACTCGGGGGCGGGGCGGCGGCGGCGGCGGCGGC  6 GGTGGCGGCCGGGGAGGGTCAGTTGGAGGCAGGCGCTCGCTGAGGC AAAAGGAGGCGCTCGGCCCGCGGCCTGACAGGGACTTAGCCCGCAG AGATCGACCCCGCGCGCGTGACCCCACACCCACCCACTCATCCATC TATCCACTCCCTGCGCCGCCTCCTCCCACCCTGAGCAGAGCCGCCG AGGATGATAAACACCCAGGACAGTAGTATTTTGCCTTTGAGTAACT GTCCCCAGCTCCAGTGCTGCAGGCACATTGTTCCAGGGCCTCTGTG GTGCTCCTGATGCCCCTCACCCACTGTCGAAGATCCCCGGTGGGCG AGGGGGCGGCAGGGATCCTTCTCTCTCAGCTCTAATATATAAGGAC GAGAAGCTCACTGTGACCCAGGACCTCCCTGTGAATGATGGAAAAC CTCACATCGTCCACTTCCAGTATGAGGTCACCGAGGTGAAGGTCTC TTCTTGGGATGCAGTCCTGTCCAGCCAGAGCCTGTTTGTAGAAATC CCAGATGGATTATTAGCTGATGGGAGCAAAGAAGGATTGTTAGCAC TGCTAGAGTTTGCTGAAGAGAAGATGAAAGTGAACTATGTCTTCAT CTGCTTCAGGAAGGGCCGAGAAGACAGAGCTCCACTCCTGAAGACC TTCAGCTTCTTGGGCTTTGAGATTGTACGTCCAGGCCATCCCTGTG TCCCCTCTCGGCCAGATGTGATGTTCATGGTTTATCCCCTGGACCA GAACTTGTCCGATGAGGACTAATAGTCATAGAGGATGCTTTACCCA AGAGCCACAGTGGGGGAAGAGGGGAAGTTAGGCAGCCCTGGGACAG ACGAGAGGGCTCCTCGCTGTCTAGGGAAGGACACTGAGGGGCTCAG GGTGAGGGTTGCCTATTGTGTTCTCGGAGTTGACTCGTTGAAATTG TTTTCCATAAAGAACAGTATAAACATATTATTCACATGTAATCACC AATAGTAAATGAAGATGTTTATGAACTGGCATTAGAAGCTTTCTAA ACTGCGCTGTGTGATGTGTTCTATCTAGCCTAGGGGAGGACATTGC CTAGAGGGGGAGGGACTGTCTGGGTTCAGGGGCATGGCCTGGAGGG CTGGTGGGCAGCACTGTCAGGCTCAGGTTTCCCTGCTGTTGGCTTT CTGTTTTGGTTATTAAGACTTGTGTATTTTCTTTCTTTGCTTCCTG TCACCCCAGGGGCTCCTGAGTATAGGCTTTTCAGTCCCTGGGCAGT GTCCTTGAGTTGTTTTTTGACACTCTTACCTGGGCTTCTCTGTGTG CATTTGCGTCTGGCCTGGAGTAAGCAGGTCCGACCCCTCCTTCTTT ACAGCTTAGTGTTATTCTGGCATTTGGTTAAGCTGGCTTAATCTGT TTAATGTTATCAGTACATTTTAAATAGGGGCATTGAAATTTACTCC CACCACCAGGGCTTTTTTGGGGGATGCCTGGGCCTTTAAAACACTA GCCAAACTCTAATTAATTCTCAAATCACTGCCAGGAGTTCTTGCTC CTGGCTGCAGGCCCAGGCCCCAAGGTCTCCTTCTTGGGGTCACAAA CAGCAGTAAGGAAGAGGAATATATAGCAACTCAGGGCCTGGGAATT GTGGGGCAATCCGTTCTTAGGGACTGGATACTTCTGGCTGGCTGAG TATAGTACTAGCTGCCTCCCCACCAGGTTCCGAGTAGTGTCTGAGA CTCTGCTCTGCAGGGCCTAGGGTAGCGCTGGGAGTGTAGAAGTGGC CTGCCCTTAACTGTTTTCACTAAACAGCTTTTTCTAAGGGGAGAGC AAGGGGGAGAGATCTAGATTGGGTGAGGGGGACGGGGATGTCAGGG AGGCAAGTGTGTTGTGTTACTGTGTCAATAAACTGATTTAAAGTTG GAAAAAAAAAAAAAA PANK2 NM_024960.4 ATGCTGGGGGAGGGGCTGGCGGCCTCGACGGCAGCTGCGGAACTAG  7 GCCGAGGGACAAAGGCTAAGTTTTTCCATGGTTTGGACTGGATATC GGTGGAACTCTGGTCAAGCTGGTATATTTTGAACCCAAAGACATCA CTGCTGAAGAAGAAGAGGAAGAAGTGGAAAGTCTTAAAAGCATTCG GAAGTACCTGACCTCCAATGTGGCTTATGGGTCTACAGGCATTCGG GACGTGCACCTCGAGCTGAAGGACCTGACTCTGTGTGGACGCAAAG GCAATCTGCACTTTATACGCTTTCCCACTCATGACATGCCTGCTTT TATTCAAATGGGCAGAGATAAAAACTTCTCGAGTCTCCACACTGTC TTTTGTGCCACTGGAGGTGGAGCGTACAAATTTGAGCAGGATTTTC TCACAATAGGTGATCTTCAGCTTTGCAAACTGGATGAACTAGATTG CTTGATCAAAGGAATTTTATACATTGACTCAGTCGGATTCAATGGA CGGTCACAGTGCTATTACTTTGAAAACCCTGCTGATTCTGAAAAGT GTCAGAAGTTACCATTTGATTTGAAAAATCCGTATCCTCTGCTTCT GGTGAACATTGGCTCAGGGGTTAGCATCTTAGCAGTATATTCCAAA GATAATTACAAACGGGTCACAGGTACTAGTCTTGGAGGAGGAACTT TTTTTGGTCTCTGCTGTCTTCTTACTGGCTGTACCACTTTTGAAGA AGCTCTTGAAATGGCATCTCGTGGAGATAGCACCAAAGTGGATAAA CTAGTACGAGATATTTATGGAGGGGACTATGAGAGGTTTGGACTGC CAGGCTGGGCTGTGGCTTCAAGCTTTGGAAACATGATGAGCAAGGA GAAGCGAGAGGCTGTCAGTAAAGAGGACCTGGCCAGAGCGACTTTG ATCACCATCACCAACAACATTGGCTCAATAGCAAGAATGTGTGCCC TTAATGAAAACATTAACCAGGTGGTATTTGTTGGAAATTTCTTGAG AATTAATACGATCGCCATGCGGCTTTTGGCATATGCTTTGGATTAT TGGTCCAAGGGGCAGTTGAAAGCACTTTTTTCGGAACACGAGGGTT ATTTTGGAGCTGTTGGAGCACTCCTTGAGCTGTTGAAGATCCCGTG ATCATTACCTGGGGAGGGGTTCCTGAAACCTTCCACAATGGGATCT GTGGACTTTCATTTTTTTAAGAGACTTACTCAATTTCATGACTGTA CTACCTGAAACAAAGTGAGAAAGGACAGGTGTATTTTTCTAAGTCA TCAAGATAAATCCTTAAGAATTCAGTCTAAATTAGCAACCAGGAAG GAAAAATATATTAAAAACAACAAAAAAGTGGCACATGTCCAGGCAG TGTGAGGATTTGCTGTATATAAGTTGCCTGCTTTGTATTTTTGAAA TCTCTGCATCACTCATTGGAAGTGCTTCTGAAGAGAGCTGCTCTGT GTTCAGTTGACTGGTTTTGTGTCCTGTTTGAACTTGCTGAATGTAA GGCAGGCTACTATGCGTTATAATCTAATCACAATTTGTCAATATGG TCTTGGCAATCATCTGTGCATTACTCTGGTTTGCATTAAGCCTGTG TGTGAACTTACTGTAAAACATGTTTTATTTCAAGGTTCTGCAAAAT TAATTGGGCAGGTTAATTGTGTACCTGAAACTTAACAAGCAGTTTT TGGAAGGGCA PLD36.3 NM_00103169 GCATCCTCTCACCGCCGGAAGCTGAACTGACTCGTCCGCGGCCGCT  8 CTACCCCAACAGGCCGCCACCAGCGAGAGTGCGGCCATAACCATCA CGTGACCGCCCACCGACACCAGCGAGAGTGCAGTCGTAACCGTCAC GTGACCGCCCACCGTCGGCCCGGCGCTCCCCTCCGCCCGAAGCTAG CAAGCGGCGCGGCCAATGAGAAAGGCGCATGCCTGGCCCCCGCCGG CCTGCAGTCTAGCCGTAGTGCGCCTGCGCGCGGCTAGGAGGGGCCG TCAGGCGGGGATACAGCCTGGAAGGTAATGCATGTCCATGGTACAC AAATTCACAAGTTTGGAGACCCTGACACACCCACCTTCTCACCTGG GCTCTGCGTATCCCCCAGCCTTGAGGGAAGATGAAGCCTAAACTGA TGTACCAGGAGCTGAAGGTGCCTGCAGAGGAGCCCGCCAATGAGCT GCCCATGAATGAGATTGAGGCGTGGAAGGCTGCGGAAAAGAAAGCC CGCTGGGTCCTGCTGGTCCTCATTCTGGCGGTTGTGGGCTTCGGAG CCCTGATGACTCAGCTGTTTCTATGGGAATACGGCGACTTGCATCT CTTTGGGCCCAACCAGCGCCCAGCCCCCTGCTATGACCCTTGCGAA GCAGTGCTGGTGGAAAGCATTCCTGAGGGCCTGGACTTCCCCAATG CCTCCACGGGGAACCCTTCCACCAGCCAGGCCTGGCTGGGCCTGCT CGCCGGTGCGCACAGCAGCCTGGACATCGCCTCCTTCTACTGGACC CTCACCAACAATGACACCCACACGCAGGAGCCCTCTGCCCAGCAGG GTGAGGAGGTCCTCCGGCAGCTGCAGACCCTGGCACCAAAGGGCGT GAACGTCCGCATCGCTGTGAGCAAGCCCAGCGGGCCCCAGCCACAG GCGGACCTGCAGGCTCTGCTGCAGAGCGGTGCCCAGGTCCGCATGG TGGACATGCAGAAGCTGACCCATGGCGTCCTGCATACCAAGTTCTG GGTGGTGGACCAGACCCACTTCTACCTGGGCAGTGCCAACATGGAC TGGCGTTCACTGACCCAGGTCAAGGAGCTGGGCGTGGTCATGTACA ACTGCAGCTGCCTGGCTCGAGACCTGACCAAGATCTTTGAGGCCTA CTGGTTCCTGGGCCAGGCAGGCAGCTCCATCCCATCAACTTGGCCC CGGTTCTATGACACCCGCTACAACCAAGAGACACCAATGGAGATCT GCCTCAATGGAACCCCTGCTCTGGCCTACCTGGCGAGTGCGCCCCC ACCCCTGTGTCCAAGTGGCCGCACTCCAGACCTGAAGGCTCTACTC AACGTGGTGGACAATGCCCGGAGTTTCATCTACGTCGCTGTCATGA ACTACCTGCCCACTCTGGAGTTCTCCCACCCTCACAGGTTCTGGCC TGCCATTGACGATGGGCTGCGGCGGGCCACCTACGAGCGTGGCGTC AAGGTGCGCCTGCTCATCAGCTGCTGGGGACACTCGGAGCCATCCA TGCGGGCCTTCCTGCTCTCTCTGGCTGCCCTGCGTGACAACCATAC CCACTCTGACATCCAGGTGAAACTCTTTGTGGTCCCCGCGGATGAG GCCCAGGCTCGAATCCCATATGCCCGTGTCAACCACAACAAGTACA TGGTGACTGAACGCGCCACCTACATCGGAACCTCCAACTGGTCTGG CAACTACTTCACGGAGACGGCGGGCACCTCGCTGCTGGTGACGCAG AATGGGAGGGGCGGCCTGCGGAGCCAGCTGGAGGCCATTTTCCTGA GGGACTGGGACTCCCCTTACAGCCATGACCTTGACACCTCAGCTGA CAGCGTGGGCAACGCCTGCCGCCTGCTCTGAGGCCCGATCCAGTGG GCAGGCCAAGGCCTGCTGGGCCCCCGCGGACCCAGGTGCTCTGGGT CACGGTCCCTGTCCCCGCGCCCCCGCTTCTGTCTGCCCCATTGTGG CTCCTCAGGCTCTCTCCCCTGCTCTCCCACCTCTACCTCCACCCCC ACCGGCCTGACGCTGTGGCCCCGGGACCCAGCAGAGCTGGGGGAGG GATCAGCCCCCAAAGAAATGGGGGTGCATGCTGGGCCTGGCCCCCT GGCCCACCCCCACTTTCCAGGGCAAAAAGGGCCCAGGGTTATAATA AGTAAATAACTTGTCTGTACAGCCTGAAAAAAAAAAAAAAAAAAA ALG9 NM_024740.2 GTCTTTTGTCCCTCGGCGGACACCGTTTGCCAGCCAAAGCTATGTC  9 TGCGCGCTCACCGACTTCATAGGGTGCCGAATTCTTTTTTCCCCAG GCTTGCCATGGCTAGTCGAGGGGCTCGGCAGCGCCTGAAGGGCAGC GGGGCCAGCAGTGGGGATACGGCCCCGGCTGCGGACAAGCTGCGGG AGCTGCTGGGCAGCCGAGAGGCGGGCGGCGCGGAGCACCGGACCGA GTTATCTGGGAACAAAGCAGGACAAGTCTGGGCACCTGAAGGATCT ACTGCTTTCAAGTGTCTGCTTTCAGCAAGGTTATGTGCTGCTCTCC TGAGCAACATCTCTGACTGTGATGAAACATTCAACTACTGGGAGCC AACACACTACCTCATCTATGGGGAAGGGTTTCAGACTTGGGAATAT TCCCCAGCATATGCCATTCGCTCCTATGCTTACCTGTTGCTTCATG CCTGGCCAGCTGCATTTCATGCAAGAATTCTACAAACTAATAAGAT TCTTGTGTTTTACTTTTTGCGATGTCTTCTGGCTTTTGTGAGCTGT ATTTGTGAACTTTACTTTTACAAGGCTGTGTGCAAGAAGTTTGGGT TGCACGTGAGTCGAATGATGCTAGCCTTCTTGGTTCTCAGCACTGG CATGTTTTGCTCATCATCAGCATTCCTTCCTAGTAGCTTCTGTATG TACACTACGTTGATAGCCATGACTGGATGGTATATGGACAAGACTT CCATTGCTGTGCTGGGAGTAGCAGCTGGGGCTATCTTAGGCTGGCC ATTCAGTGCAGCTCTTGGTTTACCCATTGCCTTTGATTTGCTGGTC ATGAAACACAGGTGGAAGAGTTTCTTTCATTGGTCGCTGATGGCCC TCATACTATTTCTGGTGCCTGTGGTGGTCATTGACAGCTACTATTA TGGGAAGTTGGTGATTGCACCACTCAACATTGTTTTGTATAATGTC TTTACTCCTCATGGACCTGATCTTTATGGTACAGAACCCTGGTATT TCTATTTAATTAATGGATTTCTGAATTTCAATGTAGCCTTTGCTTT GGCTCTCCTAGTCCTACCACTGACTTCTCTTATGGAATACCTGCTG CAGAGATTTCATGTTCAGAATTTAGGCCACCCGTATTGGCTTACCT TGGCTCCAATGTATATTTGGTTTATAATTTTCTTCATCCAGCCTCA CAAAGAGGAGAGATTTCTTTTCCCTGTGTATCCACTTATATGTCTC TGTGGCGCTGTGGCTCTCTCTGCACTTCAGCACAGTTTTCTGTACT TCCAGAAATGTTACCACTTTGTGTTTCAACGATATCGCCTGGAGCA CTATACTGTGACATCGAATTGGCTGGCATTAGGAACTGTCTTCCTG TTTGGGCTCTTGTCATTTTCTCGCTCTGTGGCACTGTTCAGAGGAT ATCACGGGCCCCTTGATTTGTATCCAGAATTTTACCGAATTGCTAC AGACCCAACCATCCACACTGTCCCAGAAGGCAGACCTGTGAATGTC TGTGTGGGAAAAGAGTGGTATCGATTTCCCAGCAGCTTCCTTCTTC CTGACAATTGGCAGCTTCAGTTCATTCCATCAGAGTTCAGAGGTCA GTTACCAAAACCTTTTGCAGAAGGACCTCTGGCCACCCGGATTGTT CCTACTGACATGAATGACCAGAATCTAGAAGAGCCATCCAGATATA TTGATATCAGTAAATGCCATTATTTAGTGGATTTGGACACCATGAG AGAAACACCCCGGGAGCCAAAATATTCATCCAATAAAGAAGAATGG ATCAGCTTGGCCTATAGACCATTCCTTGATGCTTCTAGATCTTCAA AGCTGCTGCGGGCATTCTATGTCCCCTTCCTGTCAGATCAGTATAC AGTGTACGTAAACTACACCATCCTCAAACCCCGGAAAGCAAAGCAA ATCAGGAAGAAAAGTGGAGGTTAGCAACACACCTGTGGCCCCAAAG GACAACCATCTTGTTAACTATTGATTCCAGTGACCTGACTCCCTGC AAGTCATCGCCTGTAACATTTGTAATAAAGGTCTTCTGACATGAAT ACTGGAATCTGGGTGCTCTGGGCTAGTCAAAGTCTATTTCAAAGTC TAATCAAAGTCACATTTGCTCCCTGTGTGTGTCTCTGTTCTGCATG TAAACTTTTTGCAGCTAGGCAGAGAAAGGCCCTAAAGCACAGATAG ATATATTGCTCCACATCTCATTGTTTTTCCTCTGTTCAATTATTTA CTAGACCGGAGAAGAGCAGAACCAACTTACAGGAAGAATTGAAAAT CCTGGTACTGGATGGCTGTGATAAGCTGTTCTCCACACTCTGGCCT GGCATCTGAGAACTAGCAAGCCTCTCTTAGGCCATATGGGCTTCTC CACCAAAGCTGTTTGGCAGCTCCTAGCAGACCTTCTTATTGAAATC CTCATGCTGAAAATGAACACAGCCTAGTTGCCAACCCACATGTCCT TTTCACCTCCAGCAAGACTAAGCTTCTTTAAAGCACTTCACAGGAC TAGGACCCTGTCCTGGAGCTATCTCAGGAAAAAGGTGACCATTTGA GGAACTGTGACCTAATTTTATTATAATGATGCCTCTAATTTTCATT TCCTTTACAACCAACTGTAACTATAAGGTTGTATTGCTTTTTTGTT CAGTTTTAGCATGCTATTTTTTGAATTCTAGACTCCTCCATGTGAA GATATCAACAGACAAAACTACAACTGTATAGGACATATTTGGAGAA AATTCTATCAATTGATACATTTGGATGACATCACATTTTTAAGTAA TGTAATCTGAGGCCATTGCTGAGGAAATTAAGAATTTTCCTTTTTT TTTAACCACCCCCAGTGAAAAGGATCAGTGTATATTTATAGCACCT ATTTTTTAGTTCTGTCTGTTGTGAGGCACATCCTGCATGGGGCACT TCTAGTCAAATAGGCAATGATAAGGACCTAATTAAAATGTGATAAG TGTATACTATTACTTTAAAAGCCTTTACAGTCAGTACTTCAGTTTA CAAGGCACTTTCACAGCATCTCGTTTGATCCTCACAGTCACAACAT GTGGTAGACAAGGCAGGTGATTTTTATCCCCATTTTACAGATAAGG AAACAGGCTGCGGGTGGGGAGTGAGGGGAGGTAAAGATAGTTAGTT GCCTAAGGTCACACAGCCAGTAAGTAATAGAGCTGGGACTGGAACC CAGGTTTCCTTACTCTCATCTATTGCTCCTCCATATTCCTCACTCA ACCATGAAAACATTACTTGAAAGGACTGATGAGGTTAACCAGAGAC CTAACTGATATTGTAACTTTCTATTTTAAGGAAGAATTGTGTCTGT ATTTGAGTTCTTTGGAGCCTCCAGTCTGCCTGTGTGTTAGACCAGC ACAGCAGTGCTGTGTGATGCAGCCTGACCTGTGGCAGGAAAGTAGT GCTTCTGTTTGGAAGTCATGTTCTTTTGCAGCCACACAGGATCCAA ATATCAGTACTATTCCTGTAGTCAATCTGGGGTCACATTATAGGTG CCTTATTTCCCTAAGGGTAACTGATCTGAATATCTGCAAATAGGAT GAATCTATTTTTCAGAAGTTCCATCTTTCATTTTTCTTTTTTTTTT TGAGACAGAGTCTCATTCTGTCGCCCATGCTGGAGTGCAGTGGCGC GATCTCGGCTCGCTGCAACCTCTGCCTCCCAGGTTGAAGCAATTCT CATGCCTCAGCCACCCGAGTAGCTGGGATTACAGGCATGCGCCATC ATGCCCAGCTAATTTATGTATTTTTAGTAGAGTTGGAGTTTCACCA TGTTGGCCAGGCTGGTCTTGGACTCCTGACCTCAGGTCATCCACCC GCCTCAGCCTCCCAAAGTGCTGGTATTACAGGCGTGAGCCACCGCA CCCAGCCCCATCTTTCATTTTCAAAGAGAAGGGCATTCTAATAGGA ACTGGTGCCAAGAGAGAAGAAAAGAAGTGATAACAGAAGAAATGGC TAGTTACAATATTAAAAAGCTCCTCTTTGAGATCTCCTCTGCAGGA ATATCAGAGACGGAGTTGAAGCGCTGGAGAGGTAATAGGTCTAGAC AGTACAGAACAATAACTGGGGAGTGTGTGAGGATAGACTGGGCTCC CCCTTGCTTGAAAGATCTCTGGCATTTAATTCTCAATTCTTGATTA CTATTTTCCAGTGTAAAACTAGCACATATGATCTGACTACAGGACA GAGAATTTTAAGTGAAACATTTGCCTTACTTGCAGTAATAATGTGC TGTTCTTCACAGTAGCTAAGGCCCTCTATGTTTCCCAGAGGTAAAT AAGAATCCAGGAATGGAGGTCCATCTGTGATGAATGGCTTTTTTCT AATCAAAGTAGTATAATGCTGTTTTATCTGTTTTGTCATCTTGTTT TTTTTTTTTTTTAAAAAAACAAAACCTTAATTATAATATAGCGCAA AGAAAGGCCAGGACTGATGCAGGGATTCCTTGGAAATATCAGTTCC TATCACTTTTAAAACCTGATTTTGGATCTCTCTGTTCTATGTATGT CTTTAGTGAGAGCACAATACATGGCAGAACGCTGTGCCAAATGTTA TAGGTAAGGAATATAGAAATGAATGTTTTTTGTTGTGAAGGTGTTT TCATGTGATATTTTATAAACACATTTTAAAAAATCTCCATCACTTT TTAGTATAGGAAGGATAGCTTTGCCTGGGAAAAACAGTTTCAACAC ACCTGCTCAGAGTAGCAGTTCTCCCTCAAAAAAGCAGTGTTCAGCC TGCACTGACTGTTCTGCTTGCCAAAAGGAGGAAGCATGCAAGATAC TTATTTCTCCATAGATTGTGGAGTATAGAGGGATGTGGGACTACAG ATTATTATTTTTTTTCCCCGAGACAGAGTCTTGCTCTGTCGCCCAG GTTGGAACACAATGGCACGACCTCAGCTCACTGCAACCTCTGTCTC CCGGGTTCAAGCAATTCTCCTGCTTCAGCCTCCTGAGTAGCTGGGA TTACAGGCACACACCACCACCGCACTCAGCTAATTTTTGTATTTTT AGTAGAGGTGGGGTTTTACCATGTTGGCCAGGCTGGTCTTAAACTC CTGACCTTGTAATCATCCCGCCTCGGCCTCCTAAAGTGCTAGGATT ACAGGCATGAGCCACCGCACCCGGCCCAGATAATTTTTAATAGCCT TTGATCATGGGGTGAGTGAGGGAGTAGGTATACTTGGCAAATGCAT GGTTCTCTGATTTCTAGCTCTAAAGCAGCCTTATCTGAATCCCCAA ATCTTGTGATGCTGAGTACCATTACTGAACCAGTCTGCACGGTAGG CATCTGCTACCAAAATTTACCTCCTACCTGGTAGGTGTCATCTGAT AAGAAAGAAGACAGGTTATTTTAATTTTTTGAGATAATCACAGAAA ATTGCAGCCCATACTCTTTATTACCGAATTCAAGTTTGGAAATAGA CCCTTTGTTTTAAATCATGATGGGTCTTTATCCCAATCATTTATCT GGGTCATTTTTCCAACTTTGGAGTTCTAGGAAAGAACCTTGAAAAC CTGATATGATTCTGCAGCATGAGGTCTACGGTGACCATTTGGGCAA AGCTCCAGTGGCAATCATTTATTGTGTTTTGCATTTCCTGGGATTT ATTGAAATAAGAATTCACTGTGATTATGTAGTCTTCTGGCTAGTAT CAGGCAGCTCTGCTTTTAATTTGGTTAATTTTATTTTCTCTGAAGA GGGAGAAGAGGTACAATTTAATCTTGGCCTCCACAAGCATATTAAA GCTCACGTGTTAATCAGTGCATTCTTATGCTCCTACATTAAATGCC TTGGGTAAATGGATAAATGGACATGTGCCCAGCTTTAATTTTTTTT GCAACAGAAAGATCAGACTTCCGTATGGCATCGTTGGATTTCAGAG GCTTTCTGGTGTATCTGTAAATCTGAATGTTGCCTTCTGCCAGTCT GTATAACCAGGTGATTCATGCTGCAAATGAAATCAGGAAGCAGTAA AGTGTTAAAGCAAGAGTATTGTCCAATTCACTTGTCTTCCTGATCC TTGTACTTTATTTCACGTGTCGGTGTTTACATTACATACTTATATT TCCTGTGAAAGAAAGAGTTAAATAAATTGTAGCAGTTTGA NAP1L NM_139207.2 AAAAGATATGGTGGGGTGCTTAACAGAGGAGGTTAGACACCGGCGG 10 GAACCAGAGGAGCCCAAGCGCGGCGCCTGGGCCTCGGGGCTGCAGG AGTCCTCGGTGGGGGTATGGAGGTCGCCGGGGAAGGAGGACGGTTC AGTTGCTAGGCAACCCGGCCTGGACCCGCCTCTCGCTCGCGTTGCT GGGAGACTACAAGGCCGGGAGGAGGGCGGCGAAAGGGCCCTACGTG CTGACGCTAATTGTATATGAGCGCGAGCGGCGGGCTCTTGGGTCTT TTTTAGCGCCATCTGCTCGCGGCGCCGCCTCCTGCTCCTCCCGCTG CTGCTGCCGCTGCCGCCCTGAGTCACTGCCTGCGCAGCTCCGGCCG CCTGGCTCCCCATACTAGTCGCCGATATTTGGAGTTCTTACAACAT GGCAGACATTGACAACAAAGAACAGTCTGAACTTGATCAAGATTTG GATGATGTTGAAGAAGTAGAAGAAGAGGAAACTGGTGAAGAAACAA AACTCAAAGCACGTCAGCTAACTGTTCAGATGATGCAAAATCCTCA GATTCTTGCAGCCCTTCAAGAAAGACTTGATGGTCTGGTAGAAACA CCAACAGGATACATTGAAAGCCTGCCTAGGGTAGTTAAAAGACGAG TGAATGCTCTCAAAAACCTGCAAGTTAAATGTGCACAGATAGAAGC CAAATTCTATGAGGAAGTTCACGATCTTGAAAGGAAGTATGCTGTT CTCTATCAGCCTCTATTTGATAAGCGATTTGAAATTATTAATGCAA TTTATGAACCTACGGAAGAAGAATGTGAATGGAAACCAGATGAAGA AGATGAGATTTCGGAGGAATTGAAAGAAAAGGCCAAGATTGAAGAT GAGAAAAAAGATGAAGAAAAAGAAGACCCCAAAGGAATTCCTGAAT TTTGGTTAACTGTTTTTAAGAATGTTGACTTGCTCAGTGATATGGT TCAGGAACACGATGAACCTATTCTGAAGCACTTGAAAGATATTAAA GTGAAGTTCTCAGATGCTGGCCAGCCTATGAGTTTTGTCTTAGAAT TTCACTTTGAACCCAATGAATATTTTACAAATGAAGTGCTGACAAA GACATACAGGATGAGGTCAGAACCAGATGATTCTGATCCCTTTTCT TTTGATGGACCAGAAATTATGGGTTGTACAGGGTGCCAGATAGATT GGAAAAAAGGAAAGAATGTCACTTTGAAAACTATTAAGAAGAAGCA GAAACACAAGGGACGTGGGACAGTTCGTACTGTGACTAAAACAGTT TCCAATGACTCTTTCTTTAACTTTTTTGCCCCTCCTGAAGTTCCTG AGAGTGGAGATCTGGATGATGATGCTGAAGCTATCCTTGCTGCAGA CTTCGAAATTGGTCACTTTTTACGTGAGCGTATAATCCCAAGATCA GTGTTATATTTTACTGGAGAAGCTATTGAAGATGATGATGATGATT ATGATGAAGAAGGTGAAGAAGCGGATGAGGAAGGGGAAGAAGAAGG AGATGAGGAAAATGATCCAGACTATGACCCAAAGAAGGATCAAAAC CCAGCAGAGTGCAAGCAGCAGTGAAGCAGGATGTATGTGGCCTTGA GGATAACCTGCACTGGTCTACCTTCTGCTTCCCTGGAAAGGATGAA TTTACATCATTTGACAAGCCTATTTTCAAGTTATTTGTTGTTTGTT TGCTTGTTTTTGTTTTTGCAGCTAAAATAAAAATTTCAAATACAAT TTTAGTTCTTACAAGATAATGTCTTAATTTTGTACCAATTCAGGTA GAAGTAGAGGCCTACCTTGAATTAAGGGTTATACTCAGTTTTTAAC ACATTGTTGAAGAAAAGGTACCAGCTTTGGAACGAGATGCTATACT AATAAGCAAGTGTAAAAAAAAAAAAAAAAGAGGAAGAAAATCTTAA GTGATTGATGCTGTTTTCTTTTAAAAAAAAAAAAAAAAATTCATTT TCTTTGGGTTAGAGCTAGAGAGAAGGCCCCAAGCTTCTATGGTTTC TTCTAATTCTTATTGCTTAAAGTATGAGTATGTCACTTACCCGTGC TTCTGTTTACTGTGTAATTAAAATGGGTAGTACTGTTTACCTAACT ACCTCATGGATGTGTTAAGGCATATTGAGTTAAATCTCATATAATG TTTCTCAATCTTGTTAAAAGCTCAAAATTTTGGGCCTATTTGTAAT GCCAGTGTGACACTAAGCATTTTGTTCACACCACGCTTTGATAACT AAACTGGAAAACAAAGGTGTTAAGTACCTCTGTTCTGGATCTGGGC AGTCAGCACTCTTTTTAGATCTTTGTGTGGCTCCTATTTTTATAGA AGTGGAGGGATGCACTATTTCACAAGGTCCAAGATTTGTTTTCAGA TATTTTTGATGACTGTATTGTAAATACTACAGGGATAGCACTATAG TATTGTAGTCATGAGACTTAAAGTGGAAATAAGACTATTTTTGACA AAAGATGCCATTAAATTTCAGACTGTAGAGCCACATTTACAATACC TCAGGCTAATTACTGTTAATTTTGGGGTTGAACTTTTTTTTGACAG TGAGGGTGGATTATTGGATTGTCATTAGAGGAAGGTCTAGATTTCC TGCTCTTAATAAAATTACATTGAATTGATTTTTAGAGGTAATGAAA ACTTCCTTTCTGAGAAGTTAGTGTTAAGGTCTTGGAATGTGAACAC ATTGTTTGTAGTGCTATCCATTCCTCTCCTGAGATTTTAACTTACT ACTGGAAATCCTTAACCAATTATAATAGCTTTTTTTCTTTATTTTC AAAATGATTTCCTTTGCTTTGATTAGACACTATGTGCTTTTTTTTT TTAACCATAGTTCATCGAAATGCAGCTTTTTCTGAACTTCAAAGAT AGAATCCCATTTTTAATGAACTGAAGTAGCAAAATCATCTTTTTCA TTCTTTAGGAAATAGCTATTGCCAAAGTGAAGGTGTAGATAATACC TAGTCTTGTTACATAAAGGGGATGTGGTTTGCAGAAGAATTTTCTT TATAAAATTGAAGTTTTAAGGGACGTCAGTGTTTATGCCATTTTTC CAGTTCCAAAATGATTCCATTCCATTCTAGAAATTTGAAGTATGTA ACCTGAAATCCTTAATAAAATTTGGATTTAATTTTATAAAATGTAC TGGTGATATTTTGGGTGTTTTTTTTTAAATGAATGTATATACTTTT TTTTTGAAGAGTGGAGAGTAGTGATGTCTAGAGGGAGCTATTTTGT GCTGAGGCCACTATGTTCTGTAAATATATAATTTTAAGAGCAACCT CACAATCCCTGCTAAGTGGAGTTTATTATTTGAAGACTAAAATGGA ATTCCATAGTTCCTGATAGGTTATATTCTGGGTTATTATTCTGAGT TATCTACAAACATTTTTGAGATTTGTCTTTACACTCTGATTGTAGT TTCCAGCAGCCCATGCACACTGCCAAGTAAGTCTCATTTTTTCCTG TTAGAAATGGTGAAATATCATATAATCACTTATAAAGAAAACTGAT ATGAAAAAATTTTAGAGTTGTTTGCTTTATGGTCACTCAAGTAGGG TAAGTGTTCCACAAATTCCACAAGTTGATAGTTTAACATGGATGTC TGAAAGCCACATATATAATTTCTTAGGATTCTTAAATTAGTAAATC TAGCTTACTGAAGCAGTATTAGCATCACTATTTTAGATTGCAAAAA TACCTTAATTGTGTGGAACTGGCTTGTAGAGTGGTACTTAAGAAAA ATGGGATTCTACCTCTATTTCTGTTTTAGCACACTTAATCAGGAAA GGATATATTAACTTTCATAAAAATATTTTTGTTGTGTGAATAGGTT AATGATATGGTAAGGCCCCTAAAATAACTGAATTAATTGTTTATTG TAATTGTAGGCCATTCCCATTATTAAAAATAAAGACAAAACTTGAA GTAACTGAAAATCTTATCGTGCTATGTAGAAATATTGAACTAATAT TCAAATATTTGAATGCTTTGGTTTCAGGGATTGGTTTAAAATTGGA GTCCTTTTTTATGGGTTAGTCTTACAAAAATTTAAGCCTTTATATT TTTGACTTTAAATCAAAACAAATGTTATTTTAAATGTACAGAATAG ATTGGTAGTGCAGAAGAGTGTAAGTTCTTCATAGGAGCTTTAGAAA AGAGAAATATGTGCTAATTCAGTTTTTTTTTAATCTGCACTGTACA TATATACTTGGTAATTATGAGCTTGATTTTGTTTTTGGAAATATGT GTTCATAATTTAGGTAATTTGCTACTTAAAGCACTAAGTCTCTGAT ACCTGAAAAGTACATGTAAATGGTGATGGTGAAATAATACTGCAGT TAACTTAATAGATGTATACTGGTGATTTTTGTATGCTGGATTAAAA CTCCAGATATTAAAATATAACCTGGATAAAAAGCC NOL3 NM_001185057 GGCATTCAGAGAGTAGATGCCAGTCCTGGGAAAGGCAGGGGAGGAG 11 AGGAGAGCCACGGCTGACGCTTGGGGACAGAAGGAGGAGCCTGAGG AGGAGACAGGACAGAGCGTCTGGAGAGGCAGGAGGACACCGAGTTC CCCGTGTTGGCCTCCAGGTCCTGTGCTTGCGGAGCCGTCCGGCGGC TGGGATCGAGCCCCGACAATGGGCAACGCGCAGGAGCGGCCGTCAG AGACTATCGACCGCGAGCGGAAACGCCTGGTCGAGACGCTGCAGGC GGACTCGGGACTGCTGTTGGACGCGCTGCTGGCGCGGGGCGTGCTC ACCGGGCCAGAGTACGAGGCATTGGATGCACTGCCTGATGCCGAGC GCAGGGTGCGCCGCCTACTGCTGCTGGTGCAGGGCAAGGGCGAGGC CGCCTGCCAGGAGCTGCTACGCTGTGCCCAGCGTACCGCGGGCGCG CCGGACCCCGCTTGGGACTGGCAGCACGCTACCGGGACCGCAGCTA TGACCCTCCATGCCCAGGCCACTGGACGCCGGAGGCACCCGGCTCG GGGACCACATGCCCCGGGTTGCCCAGAGCTTCAGACCCTGACGAGG CCGGGGGCCCTGAGGGCTCCGAGGCGGTGCAATCCGGGACCCCGGA GGAGCCAGAGCCAGAGCTGGAAGCTGAGGCCTCTAAAGAGGCTGAA CCGGAGCCGGAGCCAGAGCCAGAGCTGGAACCCGAGGCTGAAGCAG AACCAGAGCCGGAACTGGAGCCAGAACCGGACCCAGAGCCCGAGCC CGACTTCGAGGAAAGGGACGAGTCCGAAGATTCCTGAAGGCCAGAG CTCTGACAGGCGGTGCCCCGCCCATGCTGGATAGGACCTGGGATGC TGCTGGAGCTGAATCGGATGCCACCAAGGCTCGGTCCAGCCCAGTA CCGCTGGAAGTGAATAAACTCCGGAGGGTCGGACGGGACCTGGGCT CTCTCCACGATTCTGGCTGTTTGCCCAGGAACTTAGGGTGGGTACC TCTGAGTCCCAGGGACCTGGGCAGGCCCAAGCCCACCACGAGCATC ATCCAGTCCTCAGCCCTAATCTGCCCTTAGGAGTCCAGGCTGCACC CTGGAGATCCCAAACCTAGCCCCCTAGTGGGACAAGGACCTGACCC TCCTGCCCGCATACACAACCCATTTCCCCTGGTGAGCCACTTGGCA GCATATGTAGGTACCAGCTCAACCCCACGCAAGTTCCTGAGCTGAA CATGGAGCAAGGGGAGGGTGACTTCTCTCCACATAGGGAGGGCTTA GAGCTCACAGCCTTGGGAAGTGAGACTAGAAGAGGGGAGCAGAAAG GGACCTTGAGTAGACAAAGGCCACACACATCATTGTCATTACTGTT TTAATTGTCTGGCTTCTCTCTGGACTGGGAGCTCAGTGAGGATTCT GACCAGTGACTTACACAAAAGGCGCTCTATACATATTATAATATAT TCGCTTACTAAATGAATAAGGACTTTCCAAAAAAAAAAAAAAAAAA AAAAAAAAAAAA TECPR2 NM_001172631 CCCCCGGCGGAGCCAGCTGCTGCTCTTCGGTGCTGGCCCCGGTGCC 12 GGCCCCGTTGCCCAGGGAACAGGCTCCCGGCAGCCCCCGCGGCCCG GAGTCCATCCCGCCTCCTCCGGCCCGGCGGGGCCGACGAGTCCGGA GGGGCTGCCGCGGGAGCCCCCAGGTTTCCCTAGATGACAAATAAAC ATTCCTTTTCCTGCGTGAAGATAGTCTGTGGAAACCTTGGCCATGG CATCGATATCAGAGCCTGTTACATTCAGAGAGTTCTGCCCGTTGTA CTATCTCCTCAATGCCATTCCGACAAAGATCCAGAAGGGTTTCCGC TCTATCGTGGTCTATCTCACGGCCCTCGACACCAACGGGGACTACA TCGCGGTGGGCAGCAGCATCGGCATGCTCTATCTGTACTGCCGGCA CCTCAACCAGATGAGGAAGTACAACTTTGAGGGGAAGACGGAATCT ATCACTGTGGTGAAGCTGCTGAGCTGCTTTGATGACCTGGTGGCAG CAGGCACAGCCTCTGGCAGGGTTGCAGTTTTTCAACTTGTATCTTC ATTGCCAGGGAGAAATAAACAGCTTCGGAGATTTGATGTCACTGGT ATTCACAAAAATAGCATTACAGCTCTGGCTTGGAGCCCCAATGGAA TGAAATTGTTCTCTGGAGATGACAAAGGCAAAATTGTTTATTCTTC TCTGGATCTAGACCAGGGGCTCTGTAACTCCCAGCTGGTGTTGGAG GAGCCATCTTCCATTGTGCAGCTGGATTATAGCCAGAAAGTGCTGC TGGTCTCTACTCTGCAAAGAAGTCTGCTCTTTTACACTGAAGAAAA GTCTGTAAGGCAAATTGGAACACAACCAAGGAAAAGTACTGGGAAA TTTGGTGCTTGTTTTATACCAGGACTCTGTAAGCAAAGTGATCTAA CCTTGTATGCGTCACGGCCCGGGCTCCGGCTATGGAAGGCTGATGT CCACGGGACTGTTCAAGCCACGTTTATCTTAAAAGATGCTTTTGCC GGGGGAGTCAAGCCTTTTGAACTGCACCCGCGTCTGGAATCCCCCA ACAGTGGAAGTTGCAGCTTACCTGAGAGGCACCTGGGGCTTGTTTC ATGTTTCTTTCAAGAAGGCTGGGTGCTGAGTTGGAATGAATATAGT ATCTATCTCCTAGACACAGTCAACCAGGCCACAGTTGCTGGTTTGG AAGGATCCGGTGATATTGTGTCTGTTTCGTGCACAGAAAATGAAAT ATTTTTCTTGAAAGGAGATAGGAACATTATAAGAATTTCAAGCAGG CCTGAAGGATTAACATCAACAGTGAGAGATGGTCTGGAGATGTCTG GATGCTCAGAGCGTGTCCACGTGCAGCAAGCGGAGAAGCTGCCAGG GGCCACAGTTTCTGAGACGAGGCTCAGAGGCTCTTCCATGGCCAGC TCCGTGGCCAGCGAGCCAAGGAGCAGGAGCAGCTCGCTCAACTCCA CCGACAGCGGCTCCGGGCTCCTGCCCCCTGGGCTCCAGGCCACCCC TGAGCTGGGCAAGGGCAGCCAGCCCCTGTCACAGAGATTCAACGCC ATCAGCTCAGAGGACTTTGACCAGGAGCTTGTCGTGAAGCCTATCA AAGTGAAAAGGAAGAAGAAGAAGAAGAAGACAGAAGGTGGAAGCAG GAGCACCTGTCACAGCTCCCTGGAATCGACACCCTGCTCCGAATTT CCTGGGGACAGTCCCCAGTCCTTGAACACAGACTTGCTGTCGATGA CCTCAAGTGTCCTGGGCAGTAGCGTGGATCAGTTAAGTGCAGAGTC TCCAGACCAGGAAAGCAGCTTCAATGGTGAAGTGAACGGTGTCCCA CAGGAAAATACTGACCCCGAAACGTTTAATGTCCTGGAGGTGTCAG GATCAATGCCTGATTCTCTGGCTGAGGAAGATGACATTAGAACTGA AATGCCACACTGTCACCATGCACATGGGCGGGAGCTGCTCAATGGA GCGAGGGAAGATGTGGGAGGCAGTGATGTCACGGGACTCGGAGATG AGCCGTGTCCTGCAGATGATGGACCAAATAGCACACAGTTACCCTT CCAAGAACAGGACAGCTCTCCTGGGGCGCATGATGGGGAAGACATC CAACCCATTGGCCCCCAAAGCACTTTTTGTGAAGTCCCCCTCCTGA ACTCACTCACTGTGCCTTCCAGCCTCAGCTGGGCCCCAAGTGCTGA ACAGTGGCTGCCTGGGACCAGAGCTGATGAAGGCAGCCCCGTGGAG CCCAGCCAAGAGCAGGACATCCTAACCAGCATGGAGGCCTCTGGCC ACCTCAGCACAAATCTCTGGCATGCTGTCACTGATGATGACACAGG TCAGAAAGAAATACCCATTTCTGAACGTGTCTTGGGGAGTGTGGGA GGACAGCTGACTCCGGTCTCTGCCTTGGCAGCCAGCACTCACAAGC CCTGGCTTGAGCAGCCTCCACGGGATCAGACATTGACGTCCAGCGA TGAGGAGGACATCTATGCCCACGGGCTTCCTTCTTCATCCTCAGAG ACGAGTGTGACAGAGCTCGGACCTAGTTGCTCCCAGCAGGACCTGA GCCGGCTGGGTGCAGAGGACGCCGGGCTGCTCAAGCCAGATCAGTT TGCAGAAAGCTGGATGGGCTACTCGGGTCCCGGCTATGGCATCCTC AGCTTGGTGGTCTCCGAGAAGTATATCTGGTGCCTGGACTACAAAG GCGGCCTGTTCTGCAGCGCGTTGCCGGGCGCCGGGCTGCGCTGGCA GAAGTTTGAAGATGCTGTCCAGCAGGTGGCAGTCTCGCCCTCAGGA GCCCTTCTCTGGAAGATTGAACAGAAATCTAACCGGGCTTTTGCTT GTGGGAAAGTCACCATCAAGGGGAAGCGGCACTGGTACGAAGCCCT GCCCCAGGCAGTGTTTGTGGCCCTGAGCGATGACACGGCCTGGATC ATCAGGACCAGTGGGGACCTATACTTGCAGACAGGTCTGAGCGTGG ATCGCCCTTGTGCCAGAGCCGTAAAGGTGGACTGTCCCTACCCGCT GTCCCAGATCACAGCCCGGAACAATGTGGTGTGGGCGCTGACAGAG CAGAGGGCCCTCCTGTACCGGGAGGGCGTGAGCAGCTTCTGTCCGG AAGGCGAGCAGTGGAAGTGTGACATTGTCAGCGAAAGGCAAGCTTT AGAACCCGTCTGCATAACGCTCGGGGATCAGCAGACTCTCTGGGCC CTGGACATCCATGGGAACCTGTGGTTCAGAACTGGCATTATTTCCA AGAAGCCCCAAGGAGATGACGACCATTGGTGGCAAGTGAGCATCAC GGACTATGTGGTGTTTGACCAGTGCAGCTTATTTCAGACGATAATC CATGCCACTCACTCGGTGGCCACAGCAGCCCAAGCCCCCGTAGAAA AGGTGGCAGATAAGCTGCGCATGGCGTTTTGGTCCCAGCAGCTTCA GTGCCAGCCAAGCCTTCTCGGGGTCAATAACAGCGGTGTCTGGATC TCCTCGGGCAAGAATGAATTCCACGTCGCTAAGGGAAGTCTCATAG GCACCTACTGGAATCATGTGGTTCCCCGTGGGACAGCTTCTGCTAC AAAATGGGCCTTTGTGTTGGCTTCTGCAGCTCCCACGAAGGAAGGA AGCTTCCTGTGGCTGTGCCAGAGCAGCAAGGACCTGTGCAGCGTCA GCGCCCAGAGCGCACAGTCGCGGCCCTCCACGGTGCAGCTGCCTCC CGAAGCCGAGATGCGCGCCTATGCCGCCTGCCAGGATGCGCTGTGG GCGCTGGACAGCCTCGGCCAGGTGTTCATCAGGACGCTCTCCAAGA GCTGCCCCACGGGCATGCACTGGACCAGGCTGGACCTCTCCCAGCT AGGAGCTGTAAAATTGACAAGCTTGGCATGTGGAAATCAGCACATC TGGGCCTGTGATTCCAGGGGTGGAGTTTACTTCCGTGTAGGGACTC AGCCTCTCAATCCCAGTCTCATGCTTCCAGCCTGGATAATGATTGA GCCACCTGTCCAGGTAAGCAGAAGTTAGCTGGTGGAACTCACTCTT CAGTAAGACAGAAACTGTGAGGATGCTGGTACTGGGAAAAAGGATC TGCACAGCCTCTAGAGGCCTCCCAGCAAATGCGGGGAGCCATGCCC CCAGGGTCTACACACTCTCGTTCATCAACATCACAACTGGAATTCG GGATTTGTGAAGTTTAGAGCTGAACAGACTGTTACAGATTATGAGT CAACACGTATATTTTCTCTTTCAAAATAATAATATTTCGTTTTTGA CTTTTTACTAAGTGAATATTATTTTTTAAATCTGCCTATATATTGG AACCTCTATTTTATAATAATAATGATAATAAATCAGTACCCAGAAG TATAAAGAAGGTAAAAGTTACTTTGAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAA

Definitions

The articles “a” and “an” are used in this disclosure to refer to one or more than one (i.e., to at least one) of the grammatical object of the article. By way of example, “an element” means one element or more than one element.

The term “and/or” is used in this disclosure to mean either “and” or “or” unless indicated otherwise.

As used herein, the terms “polynucleotide” and “nucleic acid molecule” are used interchangeably to mean a polymeric form of nucleotides of at least 10 bases or base pairs in length, either ribonucleotides or deoxynucleotides or a modified form of either type of nucleotide, and is meant to include single and double stranded forms of DNA. As used herein, a nucleic acid molecule or nucleic acid sequence that serves as a probe in a microarray analysis preferably comprises a chain of nucleotides, more preferably DNA and/or RNA. In other embodiments, a nucleic acid molecule or nucleic acid sequence comprises other kinds of nucleic acid structures such a for instance a DNA/RNA helix, peptide nucleic acid (PNA), locked nucleic acid (LNA) and/or a ribozyme. Hence, as used herein the term “nucleic acid molecule” also encompasses a chain comprising non-natural nucleotides, modified nucleotides and/or non-nucleotide building blocks which exhibit the same function as natural nucleotides.

As used herein, the terms “hybridize,” “hybridizing”, “hybridizes,” and the like, used in the context of polynucleotides, are meant to refer to conventional hybridization conditions, such as hybridization in 50% formamide/6×SSC/0.1% SDS/100 μg/ml ssDNA, in which temperatures for hybridization are above 37 degrees and temperatures for washing in 0.1×SSC/0.1% SDS are above 55 degrees C., and preferably to stringent hybridization conditions.

As used herein, the term “normalization” or “normalizer” refers to the expression of a differential value in terms of a standard value to adjust for effects which arise from technical variation due to sample handling, sample preparation, and measurement methods rather than biological variation of biomarker concentration in a sample. For example, when measuring the expression of a differentially expressed protein, the absolute value for the expression of the protein can be expressed in terms of an absolute value for the expression of a standard protein that is substantially constant in expression.

The terms “diagnosis” and “diagnostics” also encompass the terms “prognosis” and “prognostics”, respectively, as well as the applications of such procedures over two or more time points to monitor the diagnosis and/or prognosis over time, and statistical modeling based thereupon. Furthermore, the term diagnosis includes: a. prediction (determining if a patient will likely develop aggressive disease (hyperproliferative/invasive)), b. prognosis (predicting whether a patient will likely have a better or worse outcome at a pre-selected time in the future), c. therapy selection, d. therapeutic drug monitoring, and e. relapse monitoring.

The term “providing” as used herein with regard to a biological sample refers to directly or indirectly obtaining the biological sample from a subject. For example, “providing” may refer to the act of directly obtaining the biological sample from a subject (e.g., by a blood draw, tissue biopsy, lavage and the like). Likewise, “providing” may refer to the act of indirectly obtaining the biological sample. For example, providing may refer to the act of a laboratory receiving the sample from the party that directly obtained the sample, or to the act of obtaining the sample from an archive.

“Accuracy” refers to the degree of conformity of a measured or calculated quantity (a test reported value) to its actual (or true) value. Clinical accuracy relates to the proportion of true outcomes (true positives (TP) or true negatives (TN) versus misclassified outcomes (false positives (FP) or false negatives (FN)), and may be stated as a sensitivity, specificity, positive predictive values (PPV) or negative predictive values (NPV), or as a likelihood, odds ratio, among other measures.

The term “biological sample” as used herein refers to any sample of biological origin potentially containing one or more biomarkers. Examples of biological samples include tissue, organs, or bodily fluids such as whole blood, plasma, serum, tissue, lavage or any other specimen used for detection of disease.

The term “subject” as used herein refers to a mammal, preferably a human. The terms “subject” and “patient” are used interchangeably herein.

“Treating” or “treatment” as used herein with regard to a condition may refer to preventing the condition, slowing the onset or rate of development of the condition, reducing the risk of developing the condition, preventing or delaying the development of symptoms associated with the condition, reducing or ending symptoms associated with the condition, generating a complete or partial regression of the condition, or some combination thereof.

Biomarker levels may change due to treatment of the disease. The changes in biomarker levels may be measured by the present disclosure. Changes in biomarker levels may be used to monitor the progression of disease or therapy.

The term “stable disease” refers to a diagnosis for the presence of a NET, however the NET has been treated and remains in a stable condition, i.e. one that that is not progressive, as determined by imaging data and/or best clinical judgment.

The term “progressive disease” refers to a diagnosis for the presence of a highly active state of a NET, i.e. one has not been treated and is not stable or has been treated and has not responded to therapy, or has been treated and active disease remains, as determined by imaging data and/or best clinical judgment.

The terms “effective amount” and “therapeutically effective amount” of an agent or compound are used in the broadest sense to refer to a nontoxic but sufficient amount of an active agent or compound to provide the desired effect or benefit.

The term “benefit” is used in the broadest sense and refers to any desirable effect and specifically includes clinical benefit as defined herein. Clinical benefit can be measured by assessing various endpoints, e.g., inhibition, to some extent, of disease progression, including slowing down and complete arrest; reduction in the number of disease episodes and/or symptoms; reduction in lesion size; inhibition (i.e., reduction, slowing down or complete stopping) of disease cell infiltration into adjacent peripheral organs and/or tissues; inhibition (i.e. reduction, slowing down or complete stopping) of disease spread; decrease of auto-immune response, which may, but does not have to, result in the regression or ablation of the disease lesion; relief, to some extent, of one or more symptoms associated with the disorder; increase in the length of disease-free presentation following treatment, e.g., progression-free survival; increased overall survival; higher response rate; and/or decreased mortality at a given point of time following treatment.

The terms “cancer” and “cancerous” refer to or describe the physiological condition in mammals that is typically characterized by unregulated cell growth. Included in this definition are benign and malignant cancers. Examples of cancer include but are not limited to, carcinoma, lymphoma, blastoma, sarcoma, and leukemia. More particular examples of such cancers include adrenocortical carcinoma, bladder urothelial carcinoma, breast invasive carcinoma, cervical squamous cell carcinoma, endocervical adenocarcinoma, cholangiocarcinoma, colon adenocarcinoma, lymphoid neoplasm diffuse large B-cell lymphoma, esophageal carcinoma, glioblastoma multiforme, head and neck squamous cell carcinoma, kidney chromophobe, kidney renal clear cell carcinoma, kidney renal papillary cell carcinoma, acute myeloid leukemia, brain lower grade glioma, liver hepatocellular carcinoma, lung adenocarcinoma, lung squamous cell carcinoma, mesothelioma, ovarian serous cystadenocarcinoma, pancreatic adenocarcinoma, pheochromocytoma, paraganglioma, prostate adenocarcinoma, rectum adenocarcinoma, sarcoma, skin cutaneous melanoma, stomach adenocarcinoma, testicular germ cell tumors, thyroid carcinoma, thymoma, uterine carcinosarcoma, uveal melanoma. Other examples include breast cancer, lung cancer, lymphoma, melanoma, liver cancer, colorectal cancer, ovarian cancer, bladder cancer, renal cancer or gastric cancer. Further examples of cancer include neuroendocrine cancer, non-small cell lung cancer (NSCLC), small cell lung cancer, thyroid cancer, endometrial cancer, biliary cancer, esophageal cancer, anal cancer, salivary, cancer, vulvar cancer or cervical cancer.

The term “tumor” refers to all neoplastic cell growth and proliferation, whether malignant or benign, and all pre-cancerous and cancerous cells and tissues. The terms “cancer,” “cancerous,” “cell proliferative disorder,” “proliferative disorder” and “tumor” are not mutually exclusive as referred to herein.

As used in this Specification and the appended claims, the singular forms “a,” “an” and “the” include plural referents unless the context clearly dictates otherwise.

Unless specifically stated or obvious from context, as used herein, the term “or” is understood to be inclusive and covers both “or” and “and”.

EXAMPLES

The disclosure is further illustrated by the following examples, which are not to be construed as limiting this disclosure in scope or spirit to the specific procedures herein described. It is to be understood that the examples are provided to illustrate certain embodiments and that no limitation to the scope of the disclosure is intended thereby. It is to be further understood that resort may be had to various other embodiments, modifications, and equivalents thereof which may suggest themselves to those skilled in the art without departing from the spirit of the present disclosure and/or scope of the appended claims.

Example 1

Derivation of the PRRT Predictive Quotient (PPQ): An 8-Marker Gene Panel Combined with Grade

The PRRT predictive quotient (PPQ) comprises expression of genes involved in growth factor expression/metabolism (Table 2) and tissue grade. It provides two biomarker outputs—“positive” (or predict responder) and “negative” (or predict non-responder). The model was developed from an initial cohort of 54 patients and then clinically validated in four separate cohorts (n=214).

TABLE 2 Amplicon produced GEP-NEN Biomarker or NCBI Chromosome using forward and Housekeeping Gene location UniGene reverse primers Exon Symbol Name [Cytogenetic band] ID RefSeq Length (bp) Boundary ALG9 asparagine-linked Chr. 11 - Hs.503850 NM_024740.2 68 4-5 (Housekeeping glycosylation 9, alpha- 111652919-111742305 Gene) 1,2-mannosyltransferase [11q23.1] homolog ARAF1 v-raf murine sarcoma Chr. X - Hs.446641 NM_001654.3 74 10-11 3611 viral oncogene 47420578-47431320 homolog [Xp11.3] ATP6V1H ATPase, H+ Chr.8: Hs.491737 NM_015941 102 13-14 transporting, 54628115-54755850 lysosomal 50/57 kDa, [8q11.23] V1, Subunit H BRAF v-raf murine sarcoma Chr. 7 - Hs.550061 NM_004333.4 77 1-2 viral oncogene 140433812-140624564 homolog B1 [7q34] KRAS v-Ki-ras2 Kirsten rat Chr. 12 - Hs.505033 NM_004985.3 130 4-5 sarcoma viral 25358180-25403854 oncogene homolog [12p12.1] NAP1L1 nucleosome assembly Chr. 12 - Hs.524599 NM_139207.2 133 1-2 protein 1-like 1 76438672-76478738 [12q21.2] NOL3 nucleolar protein 3 Chr. 16: Hs.513667 NM_001185057 118 1-2 (apoptosis repressor 67204405-67209643 with CARD domain), [16q22.1] transcript variant 3 OAZ2 ornithine Chr. 15: Hs.713816 NM_002537 96 1-2 decarboxylase 64979773-64995462 antizyme 2 [15q22.31] PANK2 pantothenate kinase 2 Chr.20: Hs.516859 NM_024960 126 4-5 3869486-3904502 [20p13] PLD3 phospholipase D Chr.19: Hs.257008 NM_001031696 104 6-7 family, member 3, 40854332-40884390 transcript variant 1 [19q13.2] RAF1 v-raf-1 murine Chr. 3 - Hs.159130 NM_002880.3 90 7-8 leukemia viral 12625100-12705700 oncogene homolog 1 [3p25.2] TECPR2 tectonin beta-propeller Chr. 14: Hs. 195667 NM_001172631 61 12-13 repeat containing 2, 102829300-102968818 transcript variant 2 [14q32.31]

A two-step protocol (RNA isolation, cDNA production and PCR) is used to measure expression of growth factor (GF)-related genes (ARAF1, BRAF, KRAS and RAF-1), genes involved in metabolism (M) (ATP6V1H, OAZ2, PANK2 and PLD3) and optionally genes involved in proliferation (P) (NAP1L1, NOL3, and TECPR2). Expression levels were normalized to ALG9. In some embodiments, summated GF+M values ≥5.9 are scored “1”, values <5.9 are “0”. In some embodiments, summated GF+M+P values ≥10.9 are scored “1”, values <10.9 are “0”. From tissue histology, low grade (G1/G2, well-differentiated, or bronchial typical or atypical carcinoid) are scored “0”; high grade (G3, poorly differentiated) are scored “1”. The logistic regression classification was used to combine these data into a prediction model with the generation of a score for each sample. The PPQ of a sample was derived from: PPQ=39.22787−40.80341*(summated GF+M gene expression)−18.441*(grade) or PPQ=39.22787−40.80341*(summated GF+M+P gene expression)−18.441*(grade)

A binary output could be generated from the model.

(1) Responder refers to individuals predicted by the PPQ as achieving disease stabilization or demonstrating a partial response. These are scored as biomarker “positive” and exhibit p-values <0.5.

(2) A non-responder was defined as an individual exhibiting progressive disease at the time of follow-up (PRRT failure). These are considered biomarker “negative” and exhibit p-values ≥0.5.

Five examples of the output are provided in Table 3.

TABLE 3 These are examples of output from the Algorithm Summated Summated expression PPQ Sample GF expression (GF + GEP Histology Grade Logistic Classi- # Signalome* Metabolome** Proliferome*** (GF + M) M + P) Score Grade^(&) Score Regression p-value^($) fier^(#) 1 41.5 25.7 10.2 67.24 77.44 1 G1 0 −1.57554 0.0258 R 2 17.92 5.40 3.1 23.32 26.42 1 G3 1 −20.0165 9.36 × 10⁻²¹ R 3 6.33 2.07 14.8 8.405 23.205 1 Typical 0 −1.57554 0.0258 R carcinoid (lung) 4 3.93 1.94 2.1 5.87 7.97 0 G1 0 39.22787 1.0 NR 5 3.14 1.41 4.3 4.56 8.86 0 1 1 20.78687 1.0 NR *Normalized gene expression of ARAF1, BRAF, KRAS and RAF-1; **Normalized gene expression of APT61VH, OAZ2, PANK2, and PLD3; ***Normalized gene expression of NAP1L1, NOL3, and TECPR2; ^(&)Low grade (G1/G2, well-differentiated, or bronchial typical or atypical carcinoid); high grade (G3, poorly differentiated); ^($)Values > 0.5 are classified as non-responders; and ^(#)R = responder (PPQ-positive); NR = non-responder (PPQ-negative).

This model has the following metrics: Chi²=41.6, DF=2, p<0.00001, Cox & Snell R²=0.537, Nagelkerke R²=0.722.

The accuracy of the classifier is 94% in the test population. This included: 97% responders and 91% non-responders.

This cohort was increased to 72 patients. The PPQ accurately predicted responders at initial (100%) and final (100%) follow-up (Table 4). Non-responders were predicted in 65% (initial) and 84% (final) (Fishers, p=NS). Overall, at the final follow-up, 67/72 (93%) were correctly predicted. PRRT-responders were predicted in 100% and non-responders in 84% of cases (Table 4). An evaluation of progression-free survival identified that in responders predicted by PPQ, the mPFS was not reached. For those predicted not to respond, the mPFS was 8 months. This was significantly different (HR 36.4, p<0.0001) (FIG. 1 ). The sensitivity of the test was 100%, the NPV was 100%.

This model has the following metrics: Chi²=41.6, DF=2, p<0.00001, Cox & Snell R²=0.537, Nagelkerke R²=0.722.

The accuracy of the classifier is 94% in the test population. This included: 97% responders and 91% non-responders.

This cohort was increased to 72 patients. The PPQ accurately predicted responders at initial (100%) and final (100%) follow-up (Table 4). Non-responders were predicted in 65% (initial) and 84% (final) (Fishers, p=NS). Overall, at the final follow-up, 67/72 (93%) were correctly predicted. PRRT-responders were predicted in 100% and non-responders in 84% of cases (Table 4). An evaluation of progression-free survival identified that in responders predicted by PPQ, the mPFS was not reached. For those predicted not to respond, the mPFS was 8 months. This was significantly different (HR 36.4, p<0.0001) (FIG. 1 ). The sensitivity of the test was 100%, the NPV was 100%.

TABLE 4 Predictive Accuracy of PPQ in the PRRT-treated cohorts FOLLOW-UP* (AFTER PRRT) OVERALL R NR (R + NR) Se** Sp** PPV** NPV** TEST 41/41 26/31 67/72 100%  84% 89% 100%  COHORT (100%)  (84%) (93%) (n = 72) VALIDATION 28/29 14/15 42/44 97% 93% 97% 93% COHORT I (97%) (93%) (95%) (n = 44) VALIDATION 30/32 10/10 40/42 94% 100%  100%  83% COHORT II (94%) (100%)  (95%) (n = 42) OVERALL  99/102 50/56 149/158 97% 89% 94% 94% (n = 158) (97%) (89%) (94%)

In Table 4, *Follow-up was ˜6-9 months after the end of the last PRRT cycle; **Se=sensitivity, Sp=specificity, PPV=positive predictive value, NPV=negative predictive value.

Predicting Response to PRRT

Validation I (n=44): The PPQ accurately predicted responders in 97% at follow-up. Non-responders were predicted in 93% (final). Overall, 42/44 (95%) were correctly predicted (Table 4). An evaluation of survival identified the mPFS was not reached in those predicted to respond. For “non-responders”, the mPFS was 14 months (HR 17.7, p<0.0001) (FIG. 2 ). The sensitivity of the test was 97%, the NPV was 93%.

Validation II (n=42): The PPQ accurately predicted responders in 94% at follow-up. Non-responders were predicted in 100%. Overall, at the final follow-up, 40/42 (95%) were correctly predicted. PRRT-responders were predicted in 95% and non-responders in 100% (Table 4). An evaluation of survival identified the mPFS was not reached in those predicted to respond. For “non-responders”, the mPFS was 9.7 months (HR 92, p<0.0001) (FIG. 3 ). The sensitivity of the test was 94%, the NPV was 95%.

Specificity of PPQ—Predicting Response to Non-Radioactive Somatostatin

The PPQ was retrospectively determined in 28 patients treated only with SSAs. At follow-up, 15 (54%) were stable and 13 (46%) had developed progressive disease. The PPQ correctly predicted disease stabilization in 8 (53%) and progressive disease in 6 (47%, p=NS). Survival analysis identified no impact on PFS (FIG. 4 ). The sensitivity and NPV were 53% and 46%, respectively. The PPQ did not predict response to SSA.

Specificity of PPQ—Function as a Prognostic Marker

The PPQ was retrospectively determined in 100 patients included in a Registry. Analysis was undertaken on the group as a whole irrespective of treatment. At follow-up, 48 (48%) were stable and 52 (52%) had developed progressive disease. The PPQ correctly predicted disease stabilization in 32 (67%) and progressive disease in 19 (37%, p=NS). Survival analysis identified no impact on PFS (FIG. 5 ). The sensitivity and NPV were 67% and 50%. The PPQ did not function as a prognostic biomarker over the follow-up time-period.

Demonstrating Predictive Utility for PRRT

To demonstrate a biomarker is predictive of treatment, studies should evaluate biomarker levels those in whom a treatment benefit is expected as well as in those not treated with the agent. Because biomarkers may have both predictive and prognostic features, the association between a biomarker and outcome, regardless of treatment, are required to be evaluated.

A comparison of the Kaplan-Meier survival curves (PFS) between each of these cohorts is represented in FIG. 6A (predicting “responders”) and FIG. 6B (predicting “non-responders”). A “treatment effect” was only noted in those who were biomarker “positive” i.e., predicted to be a “responder” and undergoing PRRT (Validation I and Validation II cohorts). Specifically, a quantitative difference (statistically significant, p<0.0001) was noted in median PFS between the PRRT- and non-PRRT-treated groups. This effect occurred irrespective of whether they were all biomarker “positive”. In contrast, no difference in PFS was noted in the biomarker “negative” group. This effect was noted irrespective of treatment. These data demonstrate that the PPQ functions as a predictive marker.

The metrics for an idealized biomarker are included in FIGS. 6C-D. The treatment effect was only noted in those who were treated and were PPQ biomarker “positive” (FIG. 6C—these are the two validation cohorts). It is important to highlight that this particular example identifies the idealized biomarker is not prognostic. This is highlighted by the similar survival curves in the biomarker positive and negative group in the absence. A comparison of FIG. 6A (Biomarker positive) identify that the survival curves of the SSA-treated cohort and the Registry cohort (both not treated with PRRT—10 months) are the not different from the survival curves of the PRRT-treated cohorts in FIG. 6B (Biomarker negative—survival 10-15 months) confirm that the PPQ is not prognostic.

Evaluation of PPQ-Negative Patients

Clinical outcomes of patients that were identified by the PPQ to be a predicted non-responder to PRRT therapy were further analyzed. The PPQ predicted non responders that were treated with the standard 4 cycle PRRT of Lutathera exhibited a median PFS of 9 months, as shown in FIG. 7 . Conversely, PPQ predicted non responders that underwent a personalized approach where chemotherapy was added to the protocol exhibited a longer PFS of 14 months, as shown in FIG. 7 . These data demonstrate that patients with a PPQ-negative (predicted non-responder) and who have additional therapies will respond better than those on standard therapy. Thus, the PPQ can be used to identify patients that require additional agents (e.g. immune-related treatments or chemotherapy) to be used with PRRT and thereby optimize outcomes.

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EQUIVALENTS

While the present invention has been described in conjunction with the specific embodiments set forth above, many alternatives, modifications and other variations thereof will be apparent to those of ordinary skill in the art. All such alternatives, modifications and variations are intended to fall within the spirit and scope of the present invention. 

What is claimed is:
 1. A method of treating a subject with peptide receptor radiotherapy (PRRT), wherein the subject has a neuroendocrine tumor (NET), the method comprising: determining the expression level of at least 12 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 12 biomarkers, wherein the 12 biomarkers comprise ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, TECPR2, and ALG9; normalizing the expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2 to the expression level of ALG9, thereby obtaining a normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2, PLD3, NAP1L1, NOL3, and TECPR2; summing the normalized expression level of each of ARAF1, BRAF, KRAS, RAF-1, ATP6V1H, OAZ2, PANK2 PLD3, NAP1L1, NOL3, and TECPR2, thereby obtaining a summated expression level; determining a first score, wherein the first score is 1 when the summated expression level is equal to or greater than a first predetermined cutoff value, or the first score is 0 when the summated expression level is below the first predetermined cutoff value; determining a second score based on the histological grade of the NET, wherein the second score is 1 when the NET is designated high grade, or the second score is 0 when the NET is designated low grade; calculating a third score based on the following equation: Third Score=39.22787−40.80341*(First Score)−18.441*(Second Score); determining that the third score is equal to or greater than a second predetermined cutoff value, thereby identifying that the subject will be responsive to PRRT; and administering PRRT to the subject identified as being responsive to PRRT.
 2. The method of claim 1, wherein the first predetermined cutoff value is 10.9.
 3. The method of claim 1, wherein the second predetermined cutoff value is
 0. 4. The method of claim 1, wherein at least one of the at least 12 biomarkers is RNA, cDNA, or protein.
 5. The method of claim 4, wherein when the biomarker is RNA, the RNA is reverse transcribed to produce cDNA, and the produced cDNA expression level is detected.
 6. The method of claim 1, wherein the test sample comprises blood, serum, plasma, neoplastic tissue or any combination thereof.
 7. The method of claim 1, wherein the test sample comprises blood.
 8. The method of claim 1, wherein the NET is designated high grade when the NET is poorly differentiated.
 9. The method of claim 1, wherein the NET is designated low grade when the NET is well differentiated, bronchial typical carcinoid, or bronchial atypical carcinoid.
 10. The method of claim 1, wherein administering PRRT to the subject comprises administering a ¹⁷⁷Lu-based-PRRT.
 11. The method of claim 10, wherein the ¹⁷⁷Lu-based-PRRT is ¹⁷⁷ Lu-DOTA-Tyr³-Thr⁸-octreotide. 